Wireless Sensor Networking

Introduction

Wireless sensor networking (WSN) makes use of miniaturization made possible by advanced IC design to couple full wireless subsystems to sophisticated sensors, enabling people and companies to measure a myriad of things in the physical world and act on this information through IT monitoring and control systems [1]. In particular, WSNs deployed for remote area monitoring usually comprise a large number of tiny static sensing devices, which are deployed to forward data to a sink in an ad hoc manner, over a geographically wide area to sense parameters of interest. Sink is a data gathering and information processing center, which receives and gathers data from network of sensing devices which are usually randomly deployed. However, sensor nodes are constrained in energy supply and bandwidth as each sensor node is tightly power-constrained and one-off, the lifetime of WSN is limited [2]. Such constraints combined with a typical deployment of large number of sensor nodes have posed many challenges to the design and management of sensor networks.

Problem Statement

Radio transmission or reception is the most power expensive task that a node does thus these operations has more significant impact on node power consumption and lifetime than other task that a node does [3]. Mainly there are two measures taken for power saving achieved by reducing radio communication: duty-cycling and in-network processing [4]. Unlike many high performance data networks, wireless sensor networks do not require high bit rates: 10-100 Kbps of raw network bandwidth is sufficient for many applications but not all systems like surveillance systems. Routing in sensor networks is very challenging due to several characteristics that distinguish them from c...

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...d act as node scheduling protocol on other protocols. This research on node aggregation performance will also be target on multiple-sink network to evaluate performance issues and energy efficiency. As the data from different sampled group will vary, problem of redundancy will diminish which will aid on reduced data volume where data compression protocols on sink(s) will be appropriate requiring fewer resources for computation and transmission. As the issue of data routing and hopping will be reduced by mobile sink(s) or multiple static sinks, an energy expenditure test will be done on evaluating the best possible method of movement of mobile sink, position of static sink. Further possibility of use of similar data gathering techniques with least data hopping on WSN scenario instead of using locomotive robotic model will also be studied extensively on this research.