A Historical-Beacon-Aided Localization Algorithm for Mobile Sensor Networks
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):
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.
- 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.
- The HitBall Algorithm
- System : Pentium IV 2.4 GHz.
- Hard Disk : 40 GB.
- Floppy Drive : 44 Mb.
- Monitor : 15 VGA Colour.
- Mouse :
- Ram : 512 Mb.
- 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)
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.