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MODELING THE COMMUNICATION PROBLEM IN WIRELESS SENSOR NETWORKS AS A VERTEX COVER. by Maytham Safar Mohammad Taha and Sami Habib. Presented by Omar Haider Chowdhury. Overview. Introduction Deployment problems of WSN
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MODELING THE COMMUNICATION PROBLEM IN WIRELESS SENSOR NETWORKS AS A VERTEX COVER by Maytham Safar Mohammad Taha and Sami Habib Presented by Omar Haider Chowdhury
Overview • Introduction • Deployment problems of WSN • Assumption on WSN on solving the communication problem • Mathematical formulation for Communication problem • Algorithm for solving Communication problem • Future work • References
Introduction • Advancement in low power micro-electronic circuits, wireless communications and operating system have made Wireless Sensor network into a feasible platform. • Initially WSN were dominated and funded by the military applications i.e. monitoring activity in battle field. • Now it is being used in many civilian applications i.e. habitat and environmental monitoring.
Deployment problems of WSN • There are two core problems that should be considered by deployment of any wireless sensor networks. • The Coverage problem. • The Communication problem.
The Coverage problem • The Coverage problem is to place sensor devices in a service area so that the entire service area is covered. • The authors have proposed a heuristic model to that maps the coverage problem into two sub-problems: floorplan and placement. • A combined optimization of both the sub-problems results a good coverage solution.
The Communication problem • The communication problem is to select a minimal set of placed sensor devices in a service area so that the entire area is accessible by the minimal set of sensors. • Finding the minimal set of sensors is modeled as a vertex cover problem.
Assumptions on WSN in solving the communication problem • In this work it is assumed that the sensor networks consists of two types of sensor devices. • The coverage sensors • The communication sensors
The coverage sensors • It senses/monitors the surrounding environments. • Generates data packet periodically • Forwards the data from other sensors towards the second types of sensors.
The communication sensors • It collects all the data generated by the coverage sensors. • This kind of sensors have sufficient processing capability and power supply that make their communication ranges cover the whole service area.
Mathematical formulation of the Communication problem W … M 2 3 1 1 Cell H 2 3 … Demand N A service area to be monitored by WSN
Mathematical formulation of the Communication problem • The service area, A,with two dimensional width(W) and height(H) which is obstacle free. • The service area, A, is divided into N * M cells, where each cell can possibly contain a sensor device at its centre of mass.
Mathematical formulation of the communication problem(contd.) • A set of placed sensors for the coverage problem, B, and TC are given as the input of the communication problem. • Each element in the set B is a tuple, b(i), consisting of six ordered parameters, b(i) = <S(j), C(N*M), RC, SC,CR, BL>
Mathematical formulation of the communication problem(contd.) • S(j) = The sensor identification number • C(N*M) = The physical cell location of the placed sensor within the service area • RC = The radius of coverage of sensor S(j) in meters • SC = Initial installation and deployment cost in dollars ($) • CR = Communication radius, the radio signal within S(j) can reach in meters. • BL = Battery level of S(j). • TC = The ratio of the total non-overlapping radius of coverage of all placed sensors over the total service area (W*H).
Mathematical formulation of the communication problem(contd.) • Thus the communication problem involves determining a minimal subset of B, C, such that the CR’s of all selected sensors within B can reach all other sensors in C’ = B – C.
Mathematical formulation of the communication problem(contd.) • There are three possible relations between CR and RC. • CR = RC • CR < RC • CR > RC • In this paper only the relation CR > RC is considered as the previous two relations has no practical usage.
Mathematical formulation of the communication problem(contd.) S CR S10 S20 S4 Si RC S1 S5 S8
Constraints of the mathematical formulation of the problem • 1 <= |C| <= |B| / z • A sensor which is not selected as communication sensor must be in the vertex cover of some communication sensor.
Constraints of the mathematical formulation of the problem(contd.) • L <= b(i) <= U b(i) = the number of coverage sensor in vertex cover of communication sensor i • The number of overlapping sensors should be minimized.
Mathematical formulation of the communication problem(contd.) Our objective function is to achieve a minimal vertex cover as stated = 1 means a sensor device k has been allocated to be used as a vertex cover.
Algorithm begin t =0; initialize chromosomes P (t); evaluate chromosomes P (t); while (termination conditions are unsatisfied) begin t = t + 1; select P (t) from P (t-1); mutate some of P (t); crossover some of P (t); evaluate chromosomes P (t); end end
Algorithm(contd) • A genetic algorithm is used to solve this problem. • The initial population of the problem is the chromosomes generated by applying the coverage algorithm. • In each generation multiple chromosomes are stochastically selected from the current population and modified using operations mutation and crossover to form the population for the next generation. • A fitness function measures the quality of the chromosomes based on the number of communication sensors, number of chromosomes covered by their sensing and communication ranges.
Algorithm(contd) • In the evolution process relatively fit chromosomes reproduce new chromosomes and inferior chromosomes die until a desirable fitness is found.
Genetic operations • Mutation process : This operation replaces an existed communication sensor device with a new one from the list of coverage sensors. • Crossover process : This operation combines features of two selected chromosomes to form two similar chromosomes.
Chromosome representation chromosome NULL Vertex Cover NULL NULL NULL Sensor Device NULL NULL NULL
Future Direction • The methodology used to solve this problem can be improved. • Both the coverage problem and the communication problem may be solved simultaneously. • It is possible to solve both the problems in such way that energy utilization is reduced and overall cost of setting up a WSN is reduced.
