Minimizing Transmission Cost for Third-Party Information Exchange with Network Coding

Minimizing Transmission Cost for Third-Party Information Exchange with Network Coding

ABSTRACT:

In wireless networks, getting the global knowledge of channel state information (CSI, e.g., channel gain or link loss probability) is always beneficial for the nodes to optimize the network design. However, the node usually only has the local CSI between itself and other nodes, and lacks the CSI between any pair of other nodes. To enable all the nodes to get the global CSI, in this paper, we propose a network-coded third-party information exchange scheme, with an emphasis on minimizing the total transmission cost for exchanging the CSI among the nodes. We show that for a network of N nodes, if and only if any k nodes (1 _ k < N) send at least k2 packets, a feasible solution exists for third-party information exchange. Formulating the problem of feasible and optimal solutions as an integer linear programming (ILP) problem, we compute the optimal number of packets that must be transmitted by every node. Guided by the necessary and sufficient condition, we construct two practical transmission schemes: fair load (FL) scheme and proportional load (PL) scheme. A deterministic encoding strategy based on XORs coding over GF(2) is further designed to guarantee that with FL or PL scheme, each node finally can decode the complete packets. It is shown that in two specific networks, these two schemes are optimal, achieving the minimum transmission cost. In more general networks, simulation results show that PL is still close to optimal with a high probability. Finally, a distributed transmission protocol is developed, which allows FL and PL schemes to be operated in a distributed and hence scalable manner.

 EXISTING SYSTEM:

  • Network coding, a cross-layer technology that was initially developed for static (wireline) networks has received extensive research attention in wireless community, due to its significant benefits in improving wireless performance including throughput, reliability and etc.
  • Recent studies show that network coding can also help reduce the number of transmissions or the transmission delay/cost for general cooperative data exchange.
  • An earlier study of third-party information exchange demonstrated the existence of optimal solutions, where the optimality is measured in terms of minimizing the total number of transmissions.
  • The existing researches on cooperative data exchange mainly focus on minimizing the total number of packets required to exchange, the total transmission cost/delay or fixing the security issues.

DISADVANTAGES OF EXISTING SYSTEM:

  • The problem of third-party information exchange presents a special case of the general problem of cooperative data exchange.
  • However, finding the deterministic code design to achieve these limits for cooperative data exchange can be non-trivial as it needs very high field size, and the complication comes, in part, from the very general setup of cooperative data exchange.

PROPOSED SYSTEM:

  • In this paper, we further study network-coded third party information exchange with the objective of minimizing the total transmission cost. Different from previous works, we aim to propose an efficient and scalable transmission scheme which can tell the exact number of packets that should be sent by each node. Besides that, we also aim to design an efficient deterministic encoding strategy, which not only can achieve good performance, but also has a very low encoding/decoding complexity (e.g., with a very low coding field size). We call a deterministic coding and transmission scheme feasible if it allows all the nodes to eventually deduce all the global CSI, and we call a feasible solution optimal if it also minimizes a certain cost metric.
  • The goal of this paper is to develop constructive, feasible solutions (including how many packets for each node to transmit and how they are encoded and decoded) that are optimal with respect to the total transmission cost.
  • We construct two efficient and feasible transmission schemes, and prove that the proposed two schemes will achieve optimality (with respect to the total transmission cost) under two specific scenarios.
  • A deterministic encoding strategy is designed and can be used in combination with the proposed schemes to ensure the successful deduction of all desired packets at each node. Different from previous works on minimizing transmission cost, the proposed encoding strategy is based on XORs coding over only GF(2), which has very low complexity.
  • We also develop a practical distributed transmission protocol that enables the proposed two transmission schemes to be operated in a distributed and hence scalable manner.

ADVANTAGES OF PROPOSED SYSTEM:

  • Common control channel is available which allows reliable broadcast by any node to all the other nodes.
  • We formulate the problem of minimizing the total transmission cost as an integer linear programming (ILP) problem. We show that the optimal solution is one of “water-filling” nature, and a node with lower transmission cost should therefore send more packets than the node with higher transmission cost.
  • The deterministic encoding strategy helps in achieving good performance
  • The system is optimal with respect to the total transmission cost.
  • The system also ensures the successful deduction of all desired packets at each node.

SYSTEM ARCHITECTURE:

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.

 SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Xiumin Wang, Chau Yuen, Tiffany Jing Li, Wentu Song, and Yinlong Xu, “Minimizing Transmission Cost for Third-Party Information Exchange with Network Coding”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 6, JUNE 2015.

Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach

Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach

ABSTRACT:

In mobile ad hoc networks (MANETs), a primary requirement for the establishment of communication among nodes is that nodes should cooperate with each other. In the presence of malevolent nodes, this requirement may lead to serious security concerns; for instance, such nodes may disrupt the routing process. In this context, preventing or detecting malicious nodes launching grayhole or collaborative blackhole attacks is a challenge. This paper attempts to resolve this issue by designing a dynamic source routing (DSR)-based routing mechanism, which is referred to as the cooperative bait detection scheme (CBDS), that integrates the advantages of both proactive and reactive defense architectures. Our CBDS method implements a reverse tracing technique to help in achieving the stated goal. Simulation results are provided, showing that in the presence of malicious-node attacks, the CBDS outperforms the DSR, 2ACK, and best-effort fault-tolerant routing (BFTR) protocols (chosen as benchmarks) in terms of packet delivery ratio and routing overhead (chosen as performance metrics).

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

EXISTING SYSTEM:

DSR involves two main processes: route discovery and route maintenance. To execute the route discovery phase, the source node broadcasts a Route Request (RREQ) packet through the network. If an intermediate node has routing information to the destination in its route cache, it will reply with a RREP to the source node. When the RREQ is forwarded to a node, the node adds its address information into the route record in the RREQ packet. When destination receives the RREQ, it can know each intermediary node’s address among the route.The destination node relies on the collected routing information among the packets in order to send a reply RREP message to the source node along with the whole routing information of the established route.

DISADVANTAGES OF EXISTING SYSTEM:

  • The lack of any infrastructure added with the dynamic topology feature of MANETs make these networks highly vulnerable ble to routing attacks such as blackhole and grayhole (known as variants of blackhole attacks).
  • In this regard, the effectiveness of these approaches becomes weak when multiple malicious nodes collude together to initiate a collaborative attack, which may result to more devastating damages to the network.

PROPOSED SYSTEM:

In this paper, a mechanism [so-called cooperative bait detection scheme (CBDS)] is presented that effectively detects the malicious nodes that attempt to launch grayhole/collaborative blackhole attacks. In our scheme, the address of an adjacent node is used as bait destination address to bait malicious nodes to send a reply RREP message, and malicious nodes are detected using a reverse tracing technique. Any detected malicious node is kept in a blackhole list so that all other nodes that participate to the routing of the message are alerted to stop communicating with any node in that list. Unlike previous works, the merit of CBDS lies in the fact that it integrates the proactive and reactive defense architectures to achieve the aforementioned goal.

ADVANTAGES OF PROPOSED SYSTEM:

  • In this setting, it is assumed that when a significant drop occurs in the packet delivery ratio, an alarm is sent by the destination node back to the source node to trigger the detection mechanism again.
  • This function assists in sending the bait address to entice the malicious nodes and to utilize the reverse tracing program of the CBDS to detect the exact addresses of malicious nodes.

SYSTEM ARCHITECTURE:

BLOCK DIAGRAM:

MODULES

  • Network Topology
  • Dynamic Source Routing (DSR)
  • Cooperative Bait Detection
  • Performance Evaluation

MODULES DESCRIPTION

Network Topology

The sensor nodes are randomly distributed in a sensing field. We are using mobile ad hoc network (MANET). This is the infrastructureless network and a node can move independently. In a MANET, each node not only works as a host and also acts as a router. We can find the communication range for all nodes. Every node communicates only within the range. If suppose any node out of the range, node will not communicate those nodes or drop the packets.

Dynamic Source Routing (DSR)

In this project, we are using dynamic source routing algorithm for routing. The DSR involves two main processes: route discovery and route maintenance. The source node broadcast the RREQ through the network. If an intermediate node has the route information to the destination node in its cache, it will reply with a RREP to the source node. When a RREQ is forwarded, the node adds its address information in the RREQ packet. When destination receives the RREQ, it can know all the information about intermediate node. Then the destination will reply with RREP to the source node along with the routing information.

Cooperative Bait Detection Scheme

We propose a detection scheme called Cooperative bait detection scheme (CBDS), which aims to detect the grayhole/collaborative blackhole attacks in MANET. In this scheme, the source node randomly selects the adjacent node is used as a bait destination address to bait malicious node to send a RREP message. We can find the malicious node in the routing operation by using the reverse tracing technique. If there is any malicious node detected in the routing, send the alert message or stop the communication with any node in that list. The CBDS scheme integrates the advantages of proactive detection in the initial stage and the reactive defense architecture to achieve the goal.

Performance Evaluation

In this section, we can evaluate the performance of simulation. We are using the xgraph for evaluate the performance. We choose the three evaluation metrics: Packet delivery ratio – it is the ratio of the number of packet received at destination and number of packet sent by the source, End-to-End delay – the average time taken for a packet to be transmitted from the source to destination, Throughput – number of data received by the destination without any losses.

 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.

SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Jian-Ming Chang, Po-Chun Tsou, Isaac Woungang, Han-Chieh Chao, and Chin-Feng Lai, Member, IEEE, “Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach”, IEEE SYSTEMS JOURNAL, VOL. 9, NO. 1, MARCH 2015

Cooperative Load Balancing and Dynamic Channel Allocation for Cluster-Based Mobile Ad Hoc Networks

Cooperative Load Balancing and Dynamic Channel Allocation for Cluster-Based Mobile Ad Hoc Networks

ABSTRACT:

Mobile ad hoc networks (MANETs) are becoming increasingly common, and typical network loads considered for MANETs are increasing as applications evolve. This, in turn, increases the importance of bandwidth efficiency while maintaining tight requirements on energy consumption, delay and jitter. Coordinated channel access protocols have been shown to be well suited for highly loaded MANETs under uniform load distributions. However, these protocols are in general not as well suited for non-uniform load distributions as uncoordinated channel access protocols due to the lack of on-demand dynamic channel allocation mechanisms that exist in infrastructure based coordinated protocols. In this paper, we present a lightweight dynamic channel allocation mechanism and a cooperative load balancing strategy that are applicable to cluster based MANETs to address this problem. We present protocols that utilize these mechanisms to improve performance in terms of throughput, energy consumption and inter-packet delay variation (IPDV). Through extensive simulations we show that both dynamic channel allocation and cooperative load balancing improve the bandwidth efficiency under non-uniform load distributions compared to protocols that do not use these mechanisms as well as compared to the IEEE 802.15.4 protocol with GTS mechanism and the IEEE 802.11 uncoordinated protocol.

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

EXISTING SYSTEM:

  • A distributed dynamic channel allocation algorithm with no optimality guarantees for a network with a fixed a-priori control channel assignment.
  • Alternatively, there are various game-theoretic approaches to the channel allocation problem in ad hoc wireless networks.
  • Multichannel model the channel allocation problem in multi-hop ad hoc wireless networks as a static cooperative game, in which some players collaborate to achieve a high data rate.
  • In multi-hop wireless networks, CSMA techniques enable the same radio resources to be used in distinct locations, leading to increased bandwidth efficiencies at the cost of possible collisions due to the hidden terminal problem.
  • Different channel reservation techniques are used to tackle the hidden terminal problem. Karn use an RTS/ CTS packet exchange mechanism before the transmission of the data packet.
  • 11 distributed coordination function (DCF) uses a similar mechanism.

DISADVANTAGES OF EXISTING SYSTEM:

  • Existing approaches are not scalable
  • They not cover group communication

PROPOSED SYSTEM:

  • In this project we propose two algorithms to cope with the non-uniform load distributions in MANETs: a light weight distributed dynamic channel allocation (DCA) algorithm based on spectrum sensing, and a cooperative load balancing algorithm in which nodes select their channel access providers based on the availability of the resources.
  • We apply these two algorithms for managing non-uniform load distribution in MANETs into an energy efficient real-time coordinated MAC protocol, named MH-TRACE. In MH-TRACE, the channel access is regulated by dynamically selected cluster heads (CHs).
  • MH-TRACE has been shown to have higher throughput and to be more energy efficient compared to CSMA type protocols.
  • Although MH-TRACE incorporates spatial reuse, it does not provide any channel borrowing or load balancing mechanisms and thus does not provide optimal support to non-uniform loads.

ADVANTAGES OF PROPOSED SYSTEM:

  • Increase the throughput
  • Here we use scalable approach
  • Reduce energy consumption

 

SYSTEM ARCHITECTURE:

SYSTEM FLOW

 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.

SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Bora Karaoglu, Member, IEEE and Wendi Heinzelman, Senior Member, IEEE, “Cooperative Load Balancing and Dynamic Channel Allocation for Cluster-Based Mobile Ad Hoc Networks”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 5, MAY 2015

CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes

CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes

ABSTRACT:

Mobile ad-hoc networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is specially important on networks with sporadic contacts, such as delay tolerant networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, we propose collaborative contact-based watchdog (CoCoWa) as a collaborative approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that information about selfish nodes is quickly propagated. As shown in the paper, this collaborative approach reduces the time and increases the precision when detecting selfish nodes.

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

EXISTING SYSTEM:

The impact of node selfishness on MANETs has been studied in credit-payment scheme. In credit-payment scheme it is shown that when no selfishness prevention mechanism is present, the packet delivery rates become seriously degraded, from a rate of 80 percent when the selfish node ratio is 0, to 30 percent when the selfish node ratio is 50 percent. The number of packet losses is increased by 500 percent when the selfish node ratio increases from 0 to 40 percent. A more detailed study shows that a moderate concentration of node selfishness (starting from a 20 percent level) has a huge impact on the overall performance of MANETs, such as the average hop count, the number of packets dropped, the offered throughput, and the probability of reachability. In DTNs, selfish nodes can seriously degrade the performance of packet transmission. For example, in two-hop relay schemes, if a packet is transmitted to a selfish node, the packet is not re-transmitted, therefore being lost.

DISADVANTAGES OF EXISTING SYSTEM:

  • Increase the selfish nodes
  • Increase the packet loss
  • Reduce the throughput
  • Increase overhead
  • In DTNs, selfish nodes can seriously degrade the performance of packet transmission. For example, in two-hop relay schemes, if a packet is transmitted to a selfish node, the packet is not re-transmitted, therefore being lost.

 PROPOSED SYSTEM:

  • This project introduces Collaborative Contact-based Watchdog (CoCoWa) as a new scheme for detecting selfish nodes that combines local watchdog detections and the dissemination of this information on the network. If one node has previously detected a selfish node it can transmit this information to other nodes when a contact occurs. This way, nodes have second hand information about the selfish nodes in the network.
  • The goal of our approach is to reduce the detection time and to improve the precision by reducing the effect of both false negatives and false positives. In general, the analytical evaluation shows a significant reduction of the detection time of selfish nodes with a reduced overhead when comparing CoCoWa against a traditional watchdog.
  • The impact of false negatives and false positives is also greatly reduced. Finally, the pernicious effect of malicious nodes can be reduced using the reputation detection scheme. We also evaluate CoCoWa with real mobility scenarios using well known human and vehicular mobility traces.

ADVANTAGES OF PROPOSED SYSTEM:

  • Reduce the selfish nodes
  • Increase the throughput
  • Decrease the overhead

 SYSTEM ARCHITECTURE:

BLOCK DIAGRAM:

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.

SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Enrique Hern_andez-Orallo, Member, IEEE, Manuel David Serrat Olmos, Juan-Carlos Cano, Carlos T. Calafate, and Pietro Manzoni, Member, IEEE, “CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 6, JUNE 2015.

A Historical-Beacon-Aided Localization Algorithm for Mobile Sensor Networks

A Historical-Beacon-Aided Localization Algorithm for Mobile Sensor Networks

ABSTRACT:

Range-free localization approaches are cost-effective for mobile sensor networks (because no additional hardware support is required). However, existing range-free localization approaches for mobile sensor networks suffer from either sparse anchor node problem or high communication cost. Due to economic considerations, mobile sensor networks typically have sparse anchor nodes which makes most range-free localization algorithms inaccurate. On the other hand, due to the power limitation of mobile sensor nodes (i.e., they are battery-operated) and high power consumption by communication, high communication cost will significantly reduce the network life time. For solving these two problems, in this paper, we use historical beacons (i.e., anchor nodes’ announcements delivered in previous time slots) and received signal strength (RSS) to derive three constraints. By the aid of the three constraints, we introduce a low-communication-cost range-free localization algorithm (only one-hop beacon broadcasting is required). According to the theoretical analysis and simulation results, our three constraints can indeed improve the accuracy. Simulation results also show that our algorithm outperforms even in irregular-radio-signal environments. In addition, a hardware implementation running on sensor nodes, Octopus Xs, confirms theoretical analysis and simulation results.

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

EXISTING SYSTEM:

A range-based localization algorithm calculates locations with absolute point-to-point distances, while a range-free localization algorithm calculates locations without these distances.

DISADVANTAGES OF EXISTING SYSTEM:

  • It is impractical to equip each sensor node with a GPS device in large-scale WSNs.
  • Distance estimation techniques usually require additional expensive hardware support (e.g., angle of arrival (AoA) and time difference of arrival (TDoA)), or have low accuracy (e.g., received signal strength (RSS)-based approaches). Due to the hardware limitations of WSNs, range-free solutions are being pursued as an alternative to range-based solutions.
  • Most of prior range-free localization algorithms were designed for static sensor networks and not applicable to mobile ones.
  • Existing range-free localization approaches for mobile sensor networks usually suffer from sparse anchor node problem and high communication cost.

 PROPOSED SYSTEM:

  • In this paper, we introduce a range-free localization algorithm for mobile sensor node networks. In order to address the sparse anchor node problem and high communication cost problem, our algorithm fully utilizes the advantages of the communication ranges (of nodes), historical beacons, and RSS (of beacons), which are free of communication cost. To the best of our knowledge, our algorithm is the first one to use the RSS of historical beacons in mobile sensor node localization. Our algorithm includes three new constrained regions.
  • A constrained region is a region that can cover the location of the target normal node, e.g., the communication range of a one-hop neighboring anchor node (which is widely adopted in existing range-free algorithms.
  • The three types of RSS-constrained regions:
    • Current-current-RSS-constrained region (CC-region, for short),
    • Current-historical-RSSconstrained region (CH-region, for short), and
    • Historical-historical-RSS-constrained region (HH-region, for short).

 ADVANTAGES OF PROPOSED SYSTEM:

  • Our algorithm has low communication cost (only one-hop beacon broadcasting is required). Simulation results also show that our algorithm outperforms even in irregular-radio-signal environments.
  • According to the theoretical analysis and simulation results, the three constrained regions can indeed improve the localization accuracy.

ALGORITHM USED:

  • The HitBall Algorithm

 

SYSTEM ARCHITECTURE:

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.

 SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Jen-Feng Huang, Guey-Yun Chang, and Gen-Huey Chen, “A Historical-Beacon-Aided Localization Algorithm for Mobile Sensor Networks”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 14, NO. 6, JUNE 2015.