RescueMe: Smartphone-Based Self Rescue System for Disaster Rescue

RescueMe: Smartphone-Based Self Rescue System for Disaster Rescue

ABSTRACT:

Recent ubiquitous earthquakes have been leading to mass destruction of electrical power and cellular infrastructures, and deprive the innocent lives across the world. Due to the wide-area earthquake disaster, unavailable power and communication infrastructure, limited man-power and resource, traditional rescue operations and equipment are inefficient and time-consuming, leading to the golden hours missed. With the increasing proliferation of powerful wireless devices, like smartphones, they can be assumed to be abundantly available among the disaster victims and can act as valuable resource to coordinate disaster rescue operations. In this paper, we propose a smartphone-based self rescue system, also referred to as RescueMe, to assist the operations of disaster rescue and relief. The basic idea of RescueMe is that a set of smartphones carried by survivors trapped or buried under the collapsed infrastructure forms into a one-hop network and sends out distress signal in an energy-efficient manner to nearby rescue crews to assist rescue operations. We evaluate the proposed approach through extensive simulation experiment and compare its performance with the existing scheme TeamPhone. The simulation results show that the proposed approach can significantly reduce the schedule vacancy of broadcasting distress signal and improve the discovery probability with very little sacrifice of network lifetime, and indicate a potentially viable approach to expedite disaster rescue and relief operations.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium I3 Processor.
  • Hard Disk : 500 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 2 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE : Eclipse/Android Studio

REFERENCE:

Cong Pu, Xitong Zhou, “RescueMe: Smartphone-Based Self Rescue System for Disaster Rescue”, IEEE Conference, 2019.

FallDroid: An Automated Smart Phone based Fall Detection System using Multiple Kernel Learning

FallDroid: An Automated Smart Phone based Fall Detection System using Multiple Kernel Learning

ABSTRACT:

Common fall occurrences in the elderly population pose dramatic challenges in public healthcare domain. Adoption of an efficient and yet highly reliable automatic fall detection system may not only mitigate the adverse effects of falls through immediate medical assistance, but also profoundly improve the functional ability and confidence level of elder people. This paper presents a pervasive fall detection system developed on smart phones (SPs) namely, FallDroid that exploits a two-step algorithm proposed to monitor and detect fall events using the embedded accelerometer signals. Comprising of the threshold based method (TBM) and multiple kernel learning support vector machine (MKL-SVM), the proposed algorithm uses novel techniques to effectively identify fall-like events (such as lying on a bed or sudden stop after running) and reduce false alarms. In addition to user convenience and low power consumption, experimental results reveal that the system detects falls with high accuracy (97:8% and 91:7%), sensitivity (99:5% and 95:8%), and specificity (95:2% and 88:0%) when placed around the waist and thigh, respectively. The system also achieves the lowest false alarm rate of 1 alarm per 59 hours of usage, which is best till date.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium I3 Processor.
  • Hard Disk : 500 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 2 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE : Eclipse/Android Studio

REFERENCE:

Ahsan Shahzad, Student Member, IEEE, and Kiseon Kim, Senior Member, IEEE, “FallDroid: An Automated Smart Phone based Fall Detection System using Multiple Kernel Learning”, IEEE Transactions on Industrial Informatics, 2019.

Dating with Scambots: Understanding the Ecosystem of Fraudulent Dating Applications

Dating with Scambots: Understanding the Ecosystem of Fraudulent Dating Applications

ABSTRACT:

In this work, we are focusing on a new and yet uncovered way for malicious apps to gain profit. They claim to be dating apps. However, their sole purpose is to lure users into purchasing premium/VIP services to start conversations with other (likely fake female) accounts in the app. We call these apps as fraudulent dating apps. This paper performs a systematic study to understand the whole ecosystem of fraudulent dating apps. Specifically, we have proposed a three-phase method to detect them and subsequently comprehend their characteristics via analyzing the existing account profiles. Our observation reveals that most of the accounts are not managed by real persons, but by chatbots based on predefined conversation templates. We also analyze the business model of these apps and reveal that multiple parties are actually involved in the ecosystem, including producers who develop apps, publishers who publish apps to gain profit, and the distribution network that is responsible for distributing apps to end users. Finally, we analyze the impact of them to users (i.e., victims) and estimate the overall revenue. Our work is the first systematic study on fraudulent dating apps, and the results demonstrate the urge for a solution to protect users.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium I3 Processor.
  • Hard Disk : 500 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 2 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE : Eclipse/Android Studio

REFERENCE:

Yangyu Hu, Haoyu Wang, Member, IEEE, Yajin Zhou, Member, IEEE, Yao Guo, Member, IEEE, Li Li, Member, IEEE, Bingxuan Luo and Fangren Xu, “Dating with Scambots: Understanding the Ecosystem of Fraudulent Dating Applications”, IEEE Transactions on Dependable and Secure Computing, 2019.

Applying Simulated Annealing and Parallel Computing to the Mobile Sequential Recommendation

Applying Simulated Annealing and Parallel Computing to the Mobile Sequential Recommendation

ABSTRACT:

We speed up the solution of the mobile sequential recommendation (MSR) problem that requires searching optimal routes for empty taxi cabs through mining massive taxi GPS data. We develop new methods that combine parallel computing and the simulated annealing with novel global and local searches. While existing approaches usually involve costly offline algorithms and methodical pruning of the search space, our new methods provide direct real-time search for the optimal route without the offline preprocessing. Our methods significantly reduce computational time for the high dimensional MSR problems from days to seconds based on the real-world data as well as the synthetic ones. We efficiently provide solutions to MSR problems with thousands of pick-up points without offline training, compared to the published record of 25 pick-up points.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium I3 Processor.
  • Hard Disk : 500 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 2 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE : Eclipse/Android Studio

REFERENCE:

Zeyang Ye, Keli Xiao, Yong Ge, Yuefan Deng, “Applying Simulated Annealing and Parallel Computing to the Mobile Sequential Recommendation”, IEEE Transactions on Knowledge and Data Engineering, 2019.

An Indoor Position-Estimation Algorithm Using Smartphone IMU Sensor Data

An Indoor Position-Estimation Algorithm Using Smartphone IMU Sensor Data

ABSTRACT:

Position-estimation systems for indoor localization play an important role in everyday life. The global positioning system (GPS) is a popular positioning system, which is mainly efficient for outdoor environments. In indoor scenarios, GPS signal reception is weak. Therefore, achieving good position estimation accuracy is a challenge. To overcome this challenge, it is necessary to utilize other position estimation systems for indoor localization. However, other existing indoor localization systems, especially based on inertial measurement unit (IMU) sensor data, still face challenges such as accumulated errors from sensors and external magnetic field effects. This paper proposes a position-estimation algorithm that uses the combined features of the accelerometer, magnetometer, and gyroscope data from an IMU sensor for position estimation. In this paper, we first estimate the pitch and roll values based on a fusion of accelerometer and gyroscope sensor values. The estimated pitch values are used for step detection. The step lengths are estimated by using the pitching amplitude. The heading of the pedestrian is estimated by the fusion of magnetometer and gyroscope sensor values. Finally, the position is estimated based on the step length and heading information. The proposed pitch-based step detection algorithm achieves 2.5% error as compared with acceleration-based step detection approaches. The heading estimation proposed in this paper achieves a mean heading error of 4.72_ as compared with the azimuth- and magnetometer-based approaches. The experimental results show that the proposed position-estimation algorithm achieves a high position accuracy that significantly outperforms that of conventional estimation methods used for validation in this paper.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium I3 Processor.
  • Hard Disk : 500 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 2 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE : Eclipse/Android Studio

REFERENCE:

ALWIN POULOSE, ODONGO STEVEN EYOBU, AND DONG SEOG HAN, “An Indoor Position-Estimation Algorithm Using Smartphone IMU Sensor Data”, IEEE Access, 2019.

Achieve Privacy-Preserving Priority Classification on Patient Health Data in Remote eHealthcare System

Achieve Privacy-Preserving Priority Classification on Patient Health Data in Remote eHealthcare System

ABSTRACT:

The wireless body area network (WBAN) has attracted considerable attention and becomes a promising approach to provide a 24-h on-the-go healthcare service for users. However, it still faces many challenges on the privacy of users’ sensitive personal information and the confidentiality of healthcare center’s disease models. For this reason, many privacy-preserving schemes have been proposed in recent years. However, the efficiency and accuracy of those privacy-preserving schemes become a big issue to be solved. In this paper, we propose an efficient and privacy-preserving priority classification scheme, named PPC, for classifying patients’ encrypted data at the WBAN-gateway in a remote eHealthcare system. Specifically, to reduce the system latency, we design a non-interactive privacy-preserving priority classification algorithm, which allows the WBAN-gateway to conduct the privacy-preserving priority classification for the received users’ medical packets by itself and to relay these packets according to their priorities (criticalities). A detailed security analysis shows that the PPC scheme can achieve the priority classification and packets relay without disclosing the privacy of the users’ personal information and the confidentiality of the healthcare center’s disease models. In addition, the extensive experiments with an android app and two java server programs demonstrate its efficiency in terms of computational costs and communication overheads.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium I3 Processor.
  • Hard Disk : 500 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 2 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE : Eclipse/Android Studio

REFERENCE:

GUOMING WANG, RONGXING LU, (Senior Member, IEEE), AND YONG LIANG GUAN, (Senior Member, IEEE), “Achieve Privacy-Preserving Priority Classification on Patient Health Data in Remote eHealthcare System”,  IEEE Access, 2019.

Android | EPLQ: Efficient Privacy-Preserving Location-Based Query Over Outsourced Encrypted Data

Android | EPLQ: Efficient Privacy-Preserving Location-Based Query Over Outsourced Encrypted Data

EPLQ: Efficient Privacy-Preserving Location-Based Query Over Outsourced Encrypted Data

ABSTRACT:

With the pervasiveness of smart phones, location based services (LBS) have received considerable attention and become more popular and vital recently. However, the use of LBS also poses a potential threat to user’s location privacy. In this paper, aiming at spatial range query, a popular LBS providing information about points of interest (POIs) within a given distance, we present an efficient and privacy-preserving location-based query solution, called EPLQ. Specifically, to achieve privacy preserving spatial range query, we propose the first predicate-only encryption scheme for inner product range (IPRE), which can be used to detect whether a position is within a given circular area in a privacy-preserving way. To reduce query latency, we further design a privacy-preserving tree index structure in EPLQ. Detailed security analysis confirms the security properties of EPLQ. In addition, extensive experiments are conducted, and the results demonstrate that EPLQ is very efficient in privacy preserving spatial range query over outsourced encrypted data. In particular, for a mobile LBS user using an Android phone, around 0.9 s is needed to generate a query, and it also only requires a commodity workstation, which plays the role of the cloud in our experiments, a few seconds to search POIs.

OUTPUT VIDEO:

EXISTING SYSTEM:

  • Recently, there are already some solutions for privacy preserving spatial range query.
  • Protecting the privacy of user location in LBS has attracted considerable interest. However, significant challenges still remain in the design of privacy-preserving LBS, and new challenges arise particularly due to data outsourcing. In recent years, there is a growing trend of outsourcing data including LBS data because of its financial and operational benefits.
  • Lying at the intersection of mobile computing and cloud computing, designing privacy-preserving outsourced spatial range query faces the challenges.

DISADVANTAGES OF EXISTING SYSTEM:

  • Challenge on querying encrypted LBS data. The LBS provider is not willing to disclose its valuable LBS data to the cloud. The LBS provider encrypts and outsources private LBS data to the cloud, and LBS users query the encrypted data in the cloud. As a result, querying encrypted LBS data without privacy breach is a big challenge, and we need to protect not only the user locations from the LBS provider and cloud but also LBS data from the cloud.
  • Challenge on the resource consumption in mobile devices. Many LBS users are mobile users, and their terminals are smart phones with very limited resources. However, the cryptographic or privacy-enhancing techniques used to realize privacy-preserving query usually result in high computational cost and/or storage cost at user side.
  • Challenge on the efficiency of POI searching. Spatial range query is an online service, and LBS users are sensitive to query latency. To provide good user experiences, the POI search performing at the cloud side must be done in a short time (e.g., a few seconds at most). Again, the techniques used to realize privacy-preserving query usually increase the search latency.
  • Challenge on security. LBS data are about POIs in real world. It is reasonable to assume that the attacker may have some knowledge about original LBS data. With such knowledge, known-sample attacks are possible.

PROPOSED SYSTEM:

  • In this paper, we propose an efficient solution for privacy-preserving spatial range query named EPLQ, which allows queries over encrypted LBS data without disclosing user locations to the cloud or LBS provider.
  • To protect the privacy of user location in EPLQ, we design a novel predicate-only encryption scheme for inner product range (IPRE scheme for short), which, to the best of our knowledge, is the first predicate/predicate-only scheme of this kind. To improve the performance, we also design a privacypreserving index structure named ˆ ss-tree. Specifically, the main contributions of this paper are three folds.
  • We propose IPRE, which allows testing whether the inner product of two vectors is within a given range without disclosing the vectors. In predicate encryption, the key corresponding to a predicate f can decrypt a ciphertext if and only if the attribute of the ciphertext x satisfies the predicate, i.e., f(x) = 1. Predicate-only encryption is a special type of predicate encryption not designed for encrypting/decrypting messages. Instead, it reveals that whether f(x) = 1 or not. Predicate-only encryption schemes supporting different types of predicates have been proposed for privacy-preserving query on outsourced data.
  • We propose EPLQ, an efficient solution for privacy preserving spatial range query. In particular, we show that whether a POI matches a spatial range query or not can be tested by examining whether the inner product of two vectors is in a given range. The two vectors contain the location information of the POI and the query, respectively. Based on this discovery and our IPRE scheme, spatial range query without leaking location information can be achieved. To avoid scanning all POIs to find matched POIs, we further exploit a novel index structure named ˆ ss-tree, which conceals sensitive location information with our IPRE scheme.
  • Our techniques can be used for more kinds of privacypreserving queries over outsourced data. In the spatial range query discussed in this work, we consider Euclidean distance, which is widely used in spatial databases. Our IPRE scheme and ˆ ss-tree may be used for searching records within a given weighted Euclidean distance or great-circle distance as well.Weighted Euclidean distance is used to measure the dissimilarity in many kinds of data, while great-circle distance is the distance of two points on the surface of a sphere.

ADVANTAGES OF PROPOSED SYSTEM:

  • To the best of our knowledge, there does not exist predicate/predicate-only scheme supporting inner product range. Though our scheme is used for privacypreserving spatial range query in this paper, it may be applied in other applications as well.
  • Experiments on our implementation demonstrate that our solution is very efficient.
  • Moreover, security analysis shows that EPLQ is secure under known-sample attacks and ciphertext-only attacks.
  • Using great-circle distance instead of Euclidean distance for long distances on the surface of earth is more accurate. By supporting these two kinds of distances, privacy-preserving similarity query and long spatial range query can also be realized.

SYSTEM ARCHITECTURE:

ANDROID EPLQ

MODULES:

  • System Construction Module
  • LBS User
  • LBS Provider
  • Privacy-Preserving Spatial Range Query

MODULES DESCRIPTION:

System Construction Module

  • The LBS provider has abundant of LBS data, which are POI records. The LBS provider allows authorized users (i.e., LBS users) to utilize its data through location-based queries. Because of the financial and operational benefits of data outsourcing, the LBS provider offers the query services via the cloud. However, the LBS provider is not willing to disclose the valuable LBS data to the cloud. Therefore, the LBS provider encrypts the LBS data, and outsources the encrypted data to the cloud.
  • The cloud has rich storage and computing resources. It stores the encrypted LBS data from the LBS provider, and provides query services for LBS users. So, the cloud has to search the encrypted POI records in local storage to find the ones matching the queries from LBS users.
  • LBS users have the information of their own locations, and query the encrypted records of nearby POIs in the cloud. Cryptographic or privacy-enhancing techniques are usually utilized to hide the location information in the queries sent to the cloud. To decrypt the encrypted records received from the cloud, LBS users need to obtain the decryption key from the LBS provider in advance.

LBS User

  • In this Module, the mobile user sends location-based queries to the LBS provider (or called the LBS server) and receives location-based service from the provider. The mobile user queries the location based service provider about approximate k nearest points of interest on the basis of his current location. In general, the mobile user needs to submit his location to the LBS provider which then finds out and returns to the user the k nearest POIs by comparing the distances between the mobile user’s location and POIs nearby. This reveals the mobile user’s location to the LBS provider.

LBS Provider

  • In this Module, the LBS provider provides location-based services to the mobile user. LBS allows clients to query a service provider in a ubiquitous manner, in order to retrieve detailed information about points of interest (POIs) in their vicinity (e.g., restaurants, hospitals, etc.). The LBS provider processes spatial queries on the basis of the location of the mobile user. Location information collected from mobile users, knowingly and unknowingly, can reveal far more than just a user’s latitude and longitude.

Privacy-Preserving Spatial Range Query

  • In EPLQ, user queries and the sensitive location information are encrypted with IPRE scheme. A query consists of two tokens associated with two predicate vectors, which contains the LBS user’s location information. The LBS user generates two tokens for searching
  • POI records with the proposed IPRE scheme. The two tokens associated with the query area should be generated. Let Ks[0] and Ks[1] be the generated two tokens.
  • The user sends a query to the LBS Service Provider. The LBS Service Provider searches to find all leaf nodes matching the query from the user. The LBS Service Provider returns the corresponding POI records of matched leaf nodes to the user. The LBS user decrypts received POI records with the shared key of the standard encryption scheme.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium Dual Core.
  • Hard Disk : 120 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 1 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : Android,JAVA
  • Toolkit : Android 2.3 ABOVE
  • IDE :         Eclipse/Android Studio

REFERENCE:

Lichun Li, Rongxing Lu, Senior Member, IEEE, and Cheng Huang, “EPLQ: Efficient Privacy-Preserving Location-Based Query Over Outsourced Encrypted Data”, IEEE INTERNET OF THINGS JOURNAL, VOL. 3, NO. 2, APRIL 2016.

Privacy-Preserving Relative Location Based Services for Mobile Users

Privacy-Preserving Relative Location Based Services for Mobile Users

Privacy-Preserving Relative Location Based Services for Mobile Users

[youtube]https://youtu.be/OX6ZlqZ6yi8[/youtube]

ABSTRACT:

Location-aware applications have been used widely with the assistance of the latest positioning features in Smart Phone such as GPS, AGPS, etc. However, all the existing applications gather users’ geographical data and transfer them into the pertinent information to give meaning and value. For this kind of solutions, the user’s privacy and security issues might be raised because the geographical location has to be exposed to the service provider. A novel and practical solution is proposed in this article to provide the relative location of two mobile users based on their WiFi scanned results without any additional sensors. There is no privacy concern in this solution because end users will not collect and send any sensitive information to the server. This solution adopts a Client/Server (C/S) architecture, where the mobile user as a client reports the ambient WiFi APs and the server calculates the distances based on the WiFi AP’s topological relationships. A series of technologies are explored to improve the accuracy of the estimated distance and the corresponding algorithms are proposed. We also prove the feasibility with the prototype of “Circle Your Friends” System (CYFS) on Android phone which lets the mobile user know the distance between him and his social network friends.

EXISTING SYSTEM:

The rapid proliferation of smart phone technology in urban communities has enabled mobile users to utilize context aware services on their devices. Service providers take advantage of this dynamic and ever-growing technology landscape by proposing innovative context-dependent services for mobile subscribers. Location-based Services (LBS), for example, are used by millions of mobile subscribers every day to obtain location-specific information .Two popular features of location-based services are location check-ins and location sharing. By checking into a location, users can share their current location with family and friends or obtain location-specific services from third-party providers, the obtained service does not depend on the locations of other users. The other types of location-based services, which rely on sharing of locations (or location preferences) by a group of users in order to obtain some service for the whole group, are also becoming popular. According to a recent study, location sharing services are used by almost 20% of all mobile phone users. One prominent example of such a service is the taxi-sharing application, offered by a global telecom operator, where smart phone users can share a taxi with other users at a suitable location by revealing their departure and destination locations. Similarly, another popular service enables a group of users to find the most geographically convenient place to meet.

DISADVANTAGES OF EXISTING SYSTEM:

  1. Privacy of a user’s location or location preferences, with respect to other users and the third-party service provider, is a critical concern in such location-sharing-based applications. For instance, such information can be used to de-anonymize users and their availabilities, to track their preferences or to identify their social networks. For example, in the taxi-sharing application, a curious third-party service provider could easily deduce home/work location pairs of users who regularly use their service.
  2. Without effective protection, evens parse location information has been shown to provide reliable information about a users’ private sphere, which could have severe consequences on the users’ social, financial and private life. Even service providers who legitimately track users’ location information in order to improve the offered service can inadvertently harm users’ privacy, if the collected data is leaked in an unauthorized fashion or improperly shared with corporate partners.

 PROPOSED SYSTEM:

  • In the proposed system, Problem in a privacy-preserving fashion, where each user participates by providing only a single location preference to the CYFS solver or the service provider.
  • In this significantly extended version of our earlier conference paper, we evaluate the security of our proposal under various passive and active adversarial scenarios, including collusion.
  • We also provide an accurate and detailed analysis of the privacy properties of our proposal and show that our algorithms do not provide any probabilistic advantage to a passive adversary in correctly guessing the preferred location of any participant.
  • In addition to the theoretical analysis, we also evaluate the practical efficiency and performance of the proposed algorithms by means of a prototype implementation on a test bed of Nokia mobile devices. We also address the multi-preference case, where each user may have multiple prioritized location preferences.
  • We highlight the main differences, in terms of   performance, with the single preference case, and also present initial experimental results for the multi-preference implementation. Finally, by means of a targeted user study, we provide insight into the usability of our proposed solutions.

ADVANTAGES OF PROPOSED SYSTEM:

We address the privacy issue in LSBSs by focusing on a specific problem called the CYFS. Given a set of user location preferences, the CYFS is to determine a location among the proposed ones such that the maximum distance between this location and all other users’ locations is minimized, i.e. it is fair to all users.

SYSTEM ARCHITECTURE:

Privacy-Preserving Relative Location Based Services for Mobile Users

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk           : 40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Fei Ning, Zhuang Yi, Gu Jingjing, Cao Jiannong, Yang Liang, “Privacy-Preserving Relative Location Based Services for Mobile Users”, IEEE SECURITY SCHEMES AND SOLUTIONS, 2015.

Extend Your Journey: Considering Signal Strength and Fluctuation in Location-Based Applications

Extend Your Journey: Considering Signal Strength and Fluctuation in Location-Based Applications

Extend Your Journey: Considering Signal Strength and Fluctuation in Location-Based Applications

[youtube]https://youtu.be/5JmHRWj7-Ac[/youtube]

ABSTRACT:

Reducing the communication energy is essential to facilitate the growth of emerging mobile applications. In this paper, we introduce signal strength into location-based applications to reduce the energy consumption of mobile devices for data reception. First, we model the problem of data fetch scheduling, with the objective of minimizing the energy required to fetch location-based information without impacting the application’s semantics adversely. To solve the fundamental problem, we propose a dynamic-programming algorithm and prove its optimality in terms of energy savings. Then, we perform post-optimal analysis to explore the tolerance of the algorithm to signal strength fluctuations. Finally, based on the algorithm, we consider implementation issues. We have also developed a virtual tour system integrated with existing Web applications to validate the practicability of the proposed concept. The results of experiments conducted based on real-world case studies are very encouraging and demonstrate the applicability of the proposed algorithm toward signal strength fluctuations.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

Location-based applications will become more diverse and pervasive due to the potential for a range of highly personalized and context-aware services. However, the trend will lead to a significant boost in mobile data traffic and, consequently, result in further pressure on the limited battery capacity of mobile devices. Thus, reducing the communication energy is an imminent challenge in stimulating the development of emerging location-based applications. Many existing approaches leverage the complementary characteristics of Wi-Fi and 3G—i.e., WiFi to improve energy efficiency, and 3G to maintain ubiquitous connectivity. Recently, it has been observed that signal strength has a direct impact on the communication energy consumption. The communication energy per bit when the signal is weak could be as much as six times more than that when the signal is strong. This phenomenon has proved evident in both Wi-Fi and 3G. The reason for such a phenomenon results mainly from the adaptive modulation and power control employed in wireless network systems. Based on the observation, it could be promising to exploit signal strength information to reduce the communication energy of mobile devices. However, the challenge is how to exploit this observation to gain energy efficiency. In particular, signal strength may fluctuate with time due to multipath fading, so attention has to be paid to the impact of signal fluctuations on the practicability of the proposed approaches in real-world environments.

DISADVANTAGES OF EXISTING SYSTEM:

  • The significant boost in mobile data traffic and, consequently, result in further pressure on the limited battery capacity of mobile devices.
  • The communication energy per bit when the signal is weak could be as much as six times more than that when the signal is strong. This phenomenon has proved evident in both Wi-Fi and 3G. The reason for such a phenomenon results mainly from the adaptive modulation and power control employed in wireless network systems. Based on the observation, it could be promising to exploit signal strength information to reduce the communication energy of mobile devices. However, the challenge is how to exploit this observation to gain energy efficiency. In particular, signal strength may fluctuate with time due to multipath fading, so attention has to be paid to the impact of signal fluctuations on the practicability of the proposed approaches in real-world environments.

PROPOSED SYSTEM:

  • In this paper, our major contribution is to introduce signal strength into location-based applications to reduce the energy consumption of mobile devices for data reception.
  • To validate the practicability of the concept, we developed a virtual tour system comprised of an online server and a mobile application program based on Android.
  • First, we model the fundamental problem in the virtual tour system as a data fetch scheduling problem.
  • Second, we propose a dynamic-programming algorithm to solve the fundamental problem. The solution involves scheduling the fetching of location-based information at appropriate locations so as to minimize the total energy consumption. We prove that the algorithm is optimal in terms of energy savings.
  • Third, we perform post optimal analysis to explore how the algorithm responds to signal strength fluctuations, especially the fluctuation range within which the derived solution remains optimal or feasible. The analysis helps to understand the impact of signal fluctuations on the practicability of this new concept in real-world environments.
  • Fourth, we discuss technical implementation issues that arise when introducing signal strength into location-based applications for energy savings.
  • Fifth, we conducted a series of experiments in Taipei City, Taiwan, for real-world case studies. The results show that an Android smartphone of HTC EVO 3D can achieve a significant energy reduction when accessing location-based applications.
  • Finally, we discuss the limitations of our work and highlight issues that require further investigation. The concept, once proved practicable and embraced gradually, could be extended and applied to other variants of location-based applications based on the knowledge learned from this work.

ADVANTAGES OF PROPOSED SYSTEM:

  • Exploitation signal strength information has been done to reduce the communication energy of mobile devices.
  • A feasible fetch schedule that minimizes the total energy consumption for data reception
  • Through real-world case studies, we have demonstrated the practicability of introducing signal strength into location-based applications.

 SYSTEM ARCHITECTURE:

Extend Your Journey Considering Signal Strength and Fluctuation in Location-Based Applications

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk           : 40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Chih-Chuan Cheng and Pi-Cheng Hsiu, “Extend Your Journey: Considering Signal Strength and Fluctuation in Location-Based Applications”, IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 23, NO. 2, APRIL 2015.

CWC: A Distributed Computing Infrastructure Using Smartphones

CWC: A Distributed Computing Infrastructure Using Smartphones

CWC: A Distributed Computing Infrastructure Using Smartphones

ABSTRACT:

Every night, many smartphones are plugged into a power source for recharging the battery. Given the increasing computing capabilities of smartphones, these idle phones constitute a sizeable computing infrastructure. Therefore, for an enterprise which supplies its employees with smartphones, we argue that a computing infrastructure that leverages idle smartphones being charged overnight is an energy-efficient and cost-effective alternative to running certain tasks on traditional servers. While parallel execution models and schedulers exist for servers, smartphones face a unique set of technical challenges due to the heterogeneity in CPU clock speed, variability in network bandwidth, and lower availability than servers. In this paper, we address many of these challenges to develop CWC—a distributed computing infrastructure using smartphones. We implement and evaluate a prototype of CWC that employs a novel scheduling algorithm to minimize the makespan of a set of computing tasks. Our evaluations using a testbed of 18 Android phones show that CWC’s scheduler yields a makespan that is 1.6x faster than other simpler approaches.

EXISTING SYSTEM:

The existing haS Enterprise computing using smart phones. The system that is closest in spirit to CWC is CANDIS, where the authors proposed using employee smart phones (being charged) for executing enterprise applications. 2 Similar to our effort in CWC, they implemented an execution environment for Android that allows for running desktop Java applications on smart phones in an automated fashion. They also made similar observations about scheduling tasks based on computational capabilities of smart phones. While we envision similar applications and system implementation in CWC, we provide a sophisticated algorithm that minimizes the make span based on both CPU capabilities and bandwidths of smart phones, which has not been explicitly addressed in CANDIS.

DISADVANTAGES OF EXISTING SYSTEM:

  1. Bootstrapping cost of CANDIS is too high and it has high energy consumption.
  2. There is a possibility that sensitive enterprise data gets exposed when the server communicates with smartphones using residential WiFi networks.

PROPOSED SYSTEM:

In this paper, we envision building a distributed computing infrastructure using smart phones for enterprises. Our vision is based on several compelling observations including (a) enterprises provide their employees with smart phones in many cases, (b) the phones are typically unused when being charged, and (c) such an infrastructure could potentially yield significant cost benefits to the enterprise. We articulate the technical challenges in building such an infrastructure. We address many of them to design CWC, a framework that supports such an infrastructure. We have a prototype implementation of CWC on a test bed of 18 Android phones. Using this implementation, we demonstrate both the viability and efficacy of various components within CWC.

ADVANTAGES OF PROPOSED SYSTEM:

  1. CWC preserves the charging profile of smart phones via task sleeping. This is not addressed by Condor since desktop machines do not exhibit such a problem.
  2. Bootstrapping cost is reduced and it has less energy consumption.

SYSTEM ARCHITECTURE:

CWC A Distributed Computing Infrastructure Using Smartphones

ALGORITHM USED:

  • Greedy Packing Algorithm

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk           : 40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Mustafa Y. Arslan, Indrajeet Singh, Shailendra Singh, Harsha V. Madhyastha, Karthikeyan Sundaresan, Senior Member, IEEE, and Srikanth V. Krishnamurthy, Fellow, IEEE, “CWC: A Distributed Computing Infrastructure Using Smartphones”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 8, AUGUST 2015.