Adaptive multi rate awake-sleep cycle in heterogeneous sensor network

This paper proposes the use of hierarchical heterogeneous architecture multi rate adaptive awake-sleep scheduling for wireless sensor network. Hierarchical heterogeneous architecture leads to simpler designs and implementations of energy efficient protocols, a major consideration for wireless sensor networks (WSN). We define two types sensor nodes under the hierarchical heterogeneous architecture. Three different rates are considered in awakesleep scheduling. Correlation based multi rate adaptive awake-sleep cycle has been proposed both for contention and non-contention based MAC protocol. Introduction: In this paper, we study the adaptive optimal awake-sleep scheduling protocol in hierarchical heterogeneous sensor network. Life time of sensor nodes are limited in power so any energy efficiency protocol or algorithm of sensor node is the key issues in wireless sensor network (WSN). A great deal of work on energy consumption for wireless sensor network has been carried out on various issues: energy efficient source coding, energy efficient MAC, energy efficient data gathering and so on. The purpose of this course work is to study the energy efficient adaptive multi rate awake-sleep cycle in hierarchical heterogeneous network to save energy of sensor nodes which in turn increases the life time of sensor nodes [1]. In hierarchical heterogeneous network, layers of cluster are formed, in the first layer sensor nodes (low power, low memory) are used to collect data from the sensing field and the second layer of nodes whose main function is to collect data from the sensor nodes, process and relay it towards sink. The sink is the ultimate destination of data. The second layer nodes are rich in resources (high battery power, large memory etc). In this work first layer nodes are termed as normal node and second layer nodes are termed as relay node. The choice of hierarchical heterogeneous (using two types of nodes) is the valid assumption; an example of such mobile sensor applications is “smart patient assistance” system which monitors patients’ health conditions and provide them with appropriate help. Each patient wears bio-sensors which provide information on the patient’s health conditions, such as temperature, blood pressure to a central server. Another example of mobile sensor networks is a rare animal monitoring system. Each rare animal in a group to be monitored (such as elephants) has wireless sensors attached to them that monitor their activities as well as the surrounding environment (temperature, humidity). Such information is transmitted to a more powerful device attached to one individual of the group, which then relays information to a remote server via satellite. Moreover using this type of network architecture mobility can be managed easily. Finally advantage of using this type of network architecture it is easy to implement various network protocols in two different sensor nodes independently. Multiple access technique can be broadly classified which is mainly based on contention and noncontention. In this paper we will examine the awake-sleep cycle under both multiple access techniques. In contention based MAC the major sources of energy wastes are: collision, overhearing, control packet overhead, idle listening [2][3]. S-MAC reduces energy waste from all sources. In S-MAC idle listening is reduced by periodically putting nodes into sleep state. In WSN, energy is consumed by sensing, processing and in communication. The most energy is consumed by communication part. Moreover the energy consumption in communication part (radio) is broken down into two parts. The power amplifier and the other electronics [6]. So by saving energy in communication will increase the lifetime of sensor node. Power-awareness multi-rate adaptive optimal scheduling can be introduced to save energy by varying the transmission rate. In this work adaptive energy efficient awake-sleep scheduling has been carried out which is depending on the value of correlation of past and present gathered data. According to the value of correlation the sensor node will change its bit rate and as well as its duty cycle. In this paper three types of data rates are considered: higher rate (16 bits), middle rate (8 bits), lower rate (4 bits). The more higher the value of correlation the more lower the data rate and the duration of sleep time is increased in the duty cycle. The main issues of this paper are listed as follows: • Formation of hierarchical heterogeneous pre-assigned cluster. • Formation of contention based adaptive multi rate scheduling. Related work and Network topology: Network architecture plays an important role to implement energy efficient protocol in WSN. The vast majority of the existing work related to network architectures are of homogeneous in nature, i.e equal capacity in terms of sensing, computation, communication, and power [2]. On the other hand in heterogeneous network different types of sensor nodes are considered which are differ in sensing, computation and power[1]. The nodes are usually assumed to be deployed in a uniform manner (randomly or deterministically) over a specific area. There are different ways of collecting the sensing data. The simplest is direct transmission, where each sensor directly sends gathered information to the remote receiver independent of each other. A second approach is via multi-hop routing. The third approach is clustering, where sensors form dynamically with neighbouring sensors. One of the sensor in the cluster will be elected cluster head and be responsible for relaying data from each sensor in the cluster to the remote receiver. In LEACH, cluster is formed dynamically meaning each node becomes cluster head by using some algorithms[an energy efficient protocol for wireless sensor networks . Pre-assigned cluster has been formed in this course work, which consists one fixed relay node (cluster head) and several normal nodes [1]. In this paper two types of communication patterns are considered: many-to-one, many-to-many. Many-to-many communication will be performed between sensor nodes. The details of the communication pattern and the network topology will be explained in later section. In general, multi rate communication has been adopted in cellular communication to increase the bandwidth efficiency [7]. In our case we will consider multi rate as to built energy efficient communication. In our case multi rate communication will exploit the value of correlation of the gathered data between past and present events of normal sensor nodes. The higher the correlation value lower the transmission rate which ultimately results the less energy. Single Hop non contention based Many-to-One Communication In many-to-one topology two sets of sensor nodes are considered which are differ in battery power, processing power and as well as communication power (modulation, source coding, power control etc). A simple scenario of proposed work is shown in Figure 1. Figure 1. Single-hop cluster In many-to-one architecture single-hop communication exists between nodes and relay node. The flexibility of heterogeneous many-to-one architecture is that separate application specific algorithm could be developed and implemented independently both in relay node as well as normal sensors without major changes in both sensor nodes. The above mentioned network architecture could be thought as a unit box for certain application. Redundancy in sensor nodes is not crucial in certain biological application of sensor network. The maximum number of normal sensor nodes is considered 16 in pre-assigned cluster. The normal nodes should posses a certain amount of memory and data processing capabilities to calculate the correlation of past and present data. Data prevention algorithm may be implemented by introducing a counter based algorithm in each normal sensor node. When a normal sensor node is in lower rate transmission and if there is repetition of same correlation value then that particular sensor node could go to deep sleep without sending any data to relay node. In Figure 1 if all the normal sensor nodes are same type (purpose is same) and they are used for same purpose then data fusion algorithm could be implement in relay node which ultimately then reduce more transmission rate. Correlation based multi rate scheduling In this case CDMA type multiple access technique has been assumed to introduced the multi rate concept. As a result all sensor nodes will transmit to relay node. It is further assumed that nodes are perfectly synchronised with the relay node meaning the start of reception time at the relay node from all nodes at the same time. A simple scenario of correlation based multi rate adaptive scheduling for a normal sensor (single rate, middle rate, lower rate) is shown in Figure 2 Cor re la t i on va lue = . 2 C o r r e l a t i o n v a l u e = 0 . 5 Cor re la t i on va lue=1 Sleep S l e e p