Distributed Computation in Wireless Sensor Networks: Efficient Network Architectures and Applications in WSNs

Distributed Computation in Wireless Sensor Networks: Efficient Network Architectures and Applications in WSNs

Tejaswini Devanaboyina (International Institute of Information Technology, Hyderabad, India), Balakrishna Pillalamarri (International Institute of Information Technology, Hyderabad, India) and Rama Murthy Garimella (International Institute of Information Technology, Hyderabad, India)
DOI: 10.4018/IJWNBT.2015070102
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Abstract

Wireless Sensor Networks are used to perform distributed sensing in various fields like health, military, home etc where the sensor nodes communicate among themselves and do distributed computation over the sensed values to identify the occurrence of an event. The architecture for distributed computation of primitive recursive functions and median is presented in this paper. This paper assumes the no memory computational model of sensor nodes; in the architecture for primary recursive functions i.e. the sensor nodes only have two registers. This assumption is not made for the computation of median. This paper also explores the applications of wireless sensor networks in building a smart, hassle free transportation system. In purview of emerging technologies like Internet of things and Vehicular Ad Hoc networks, the transport system can be made user friendly by including itinerary planning, dynamic speed boards etc. Already research is moving in the direction of making transport system efficient and user-friendly. This paper serves as a one more step in the process of achieving it.
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1. Introduction

Wireless Sensor Networks (WSNs) consist of a set of sensor nodes that are deployed in a field and interconnected with a wireless communication network. Each of these scattered sensor nodes have the capabilities to collect data, fuse and route the data back to the sink/base station (Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam & Erdal Cayirci, 2002); (Akyildiz, Weilian, Sankarasubramaniam, Cayirci, 2001). To collect data, each of these sensor nodes makes decision based on its observation of a part of the environment and on partial a-priori information. As larger amount of sensors are deployed in harsher environment, it is important that the distributed computation should be robust and fault-tolerant. The identification of an event in a wireless sensor network should be done as fast as possible, thus the computations are done in parallel.

Here we investigate the problem of design of optimal parallel distributed computational architecture. In distributed system components located on networked computers communicate and coordinate by passing messages to perform the specified task. Similarly distributed computation is done on distributed nodes connected over the network with defined computational model. A model of computation is a formal description of a particular type of computational process. More details about computability theory can be found in the book by (Barry Cooper, 2003). This paper assumes the no memory computational model of sensor nodes in the architecture for primitive recursive functions. No memory computational model means the sensor node just has registers to store two values; whenever the sensor node receives any value from the other sensor nodes, it simply computes the function with its own measured value and the received value and passes the results to other sensor node(s).

The distributed architecture for WSN needs to be optimal from most of the following points (Rotem, Santoro & Sidney, 1985):

  • Computational complexity

  • Transmission delay required for computations

  • Deployment / Reconfiguration

  • Fault Tolerance

The rest of the paper is as follows: Section 2 describes the problem statement. Section 3 gives the optimal architecture for primitive recursive functions and discusses the class of functions, i.e. primitive recursive functions, which can be solved using grid like architecture and also the fault tolerance capability of the proposed architecture. Section 4 discusses the network architecture for distributed computation of median. Section 5 explores the possible applications of WSNs in transportation system like itinerary planning, dynamic speed boards etc, which makes it user-friendly. Finally section 6 concludes the paper.

2. Problem Statement

The problem is to define a globally optimal data structure for calculating the defined fusion function over the sensor field. The architecture should be as optimal as possible from the point of view of all the performance measures as discussed in the above section. The computational model considered is also important while defining the suitable distributed architecture. This paper assumes the no memory computational model as discussed before. Thus the problem statement is re-defined; To find the globally optimal architecture, we need to fix some of the performance measures and try to optimize the other measures. The modified problem statement is:

Given the maximum allowed delay, define the globally optimal data structure of the wireless sensor network, for the distributed computation of fusion functions of sensed values, in the no memory computational model.

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