Distributed mobility management for target tracking in mobile sensor networks

1. Distributed mobility management for target tracking in mobile sensor networks Y. Zou and K. Charkrabarty IEEE transactions on mobile computing, vol. 6, no. 8, AUG 2007 Presented by GowunJeong

2. Contents Introduction Related prior work Tracking quality improvement due to node movement Estimation of negative consequences Decision on node movement Simulation studies conclusions

3. Introduction • The characteristics of mobile ad hoc networks (MANETs) • New members can join and leave the network any time • No base station is available • It is difficult to implement sophisticated , handover and location management scheme • Each node acts as a router • Communication connectivity is usually weak due to node movements • Mobility management has node movements purposive, not random, for better target tracking • Node movements cause higher amount of energy consumption, loss of sensing coverage and loss of connectivity • A distributed technique on mobility management could promise higher efficiency than a centralised algorithm

4. Related prior work Mostly the current issues on mobility management have been focused on communication, such as personal communication services Centralised target tracking in wireless sensor networks has been studied on collaborative sensing, energy-efficient routing and management and sensor node deployment Relatively less attention has been devoted to the problem of mobility management for mobile sensor networks, which yieldsnode disconnection, loss of sensing coverage and higher energy consumption

5. Tracking quality improvement due to node movement Preliminaries Assumptions Probability of node movement to a new location

6. Preliminaries the estimated target state at time t the estimated sensor measurement at time t • The Bayesian estimation for target tracking by a centralised manner • How to adapt the above to make a local decision? Assumptions • Every node performs sensor integration locally • Sensor measurements can be obtained from the one-hop neighbourhood • Moving nodes may lose communication connectivity, some parts of sensing coverage and energy consumption efficiency while better quality of tracking

7. Assumptions A node moves at a constant speed is away from other nodes in a small enough interval has the same number of candidate locations as other nodes considers to move and evaluate only if it detects a target uses the prior of its current location to predict the sensor measurement uses the current sensor measurement from its current one-hop neighbourhood has the same neighbourhood at time t+1 as at t has collected sensor measurements from its one-hop neighbours that have also detected the target has complete knowledge about the candidate locations of its neighbourhood 7.-10. when the node performs evaluation for movement decision at time t

8. Probability of node movement to a new location To select the best location for a node i to move to information utility function Positive reward

9. Estimation of negative consequences Energy consumption Probability of a node being disconnected Potential loss of sensing coverage

10. Energy consumption a constant in units of Joules per meter a known constant representing the maximum amount of energy that the node can afford for the one-step movement A mapping from a location at time t+1 to a real number representing the energy consumption when node i decides to move to the location is in proportion to the distance between the current location and the future location as To select a destination node which minimise the energy consumption, choose one with the highest value of the following probability

11. Probability of a node being disconnected the probability that node i at possible location li is disconnected with node j at possible location lj at time t+1 The probability that node i is disconnected at time t+1 is given by The smaller the above probability, the better the node movement

12. Potential loss of sensing coverage The probability of loss of sensing coverage of node i at time t+1 is as follows The smaller the above probability, the better the node movement

13. Decision on node movement Cost evaluation Decision on movement Analysis of time complexity

14. Cost evaluation negative consequences Calculate the expected cost for node i to move location li at time t+1 with the selection rule and all the negative consequences

15. Decision on movement Selection step 1. find a set of locations that are expected to improve the target tracking Selection step 2. selects one with the minimum cost from the set obtained from the step 1

16. Analysis of time complexity # of nodes: n Target tracking algorithm: O(T) m O(mnT) O(1) O(mn) O(mnXY) where X&Y are sensing area O(m)

17. Simulation studies Static sensor network vs mobile sensor network with mobility management Random mobile sensor network vs mobile network with mobility management Localisedvscentralised implementations

18. Static sensor network vs mobile sensor network with mobility management

19. Random mobile sensor network vs mobile network with mobility management

20. Localisedvscentralised implementations

21. conclusions • A new mobility management scheme for mobile sensor networks It considers • Tracking quality • Connectivity breakage • Loss of sensing coverage • Energy consumption • A distributed implementation - only the knowledge of one-hop neighbourhood is required • The cost evaluation - target tracking quality <-> negative consequences