PERFORMANCE ANALYSIS OF CHANNEL ACCESS MODEL FOR MAC IN RANDOMLY DISTRIBUTED WIRELESS SENSOR NETWORKS

ABSTRACT Medium Access control (MAC) is one of the fundamental problems i

Optimising lower layers of the protocol stack to improve communication performance in a wireless temperature sensor network

The function of wireless sensor networks is to monitor events or gather information and report the information to a sink node, a central location or a base station. It is a requirement that the information is transmitted through the network efficiently. Wireless communication is the main activity that consumes energy in wireless sensor networks through idle listening, overhearing, interference and collision. It becomes essential to limit energy usage while maintaining communication between the sensor nodes and the sink node as the nodes die after the battery has been exhausted. Thus, conserving energy in a wireless sensor network is of utmost importance. Numerous methods to decrease energy expenditure and extend the lifetime of the network have been proposed. Researchers have devised methods to efficiently utilise the limited energy available for wireless sensor networks by optimising the design parameters and protocols. Cross-layer optimisation is an approach that has been employed to improve wireless communication. The essence of cross-layer scheme is to optimise the exchange and control of data between two or more layers to improve efficiency. The number of transmissions is therefore a vital element in evaluating overall energy usage. In this dissertation, a Markov Chain model was employed to analyse the tuning of two layers of the protocol stack, namely the Physical Layer (PHY) and Media Access Control layer (MAC), to find possible energy gains. The study was conducted utilising the IEEE 802.11 channel, SensorMAC (SMAC) and Slotted-Aloha (S-Aloha) medium access protocols in a star topology Wireless Temperature Sensor Network (WTSN). The research explored the prospective energy gains that could be realised through optimizing the Forward Error Correction (FEC) rate. Different Reed Solomon codes were analysed to explore the effect of protocol tuning on energy efficiency, namely transmission power, modulation method, and channel access. The case where no FEC code was used and analysed as the control condition. A MATLAB simulation model was used to identify the statistics of collisions, overall packets transmitted, as well as the total number of slots used during the transmission phase. The bit error probability results computed analytically were utilised in the simulation model to measure the probability of successful transmitting data in the physical layer. The analytical values and the simulation results were compared to corroborate the correctness of the models. The results indicate that energy gains can be accomplished by the suggested layer tuning approach.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Enabling Green Wireless Sensor Networks: Energy Efficient T-MAC Using Markov Chain Based Optimization

Due to the rapidly growing sensor-enabled connected world around us, with the continuously decreasing size of sensors from smaller to tiny, energy efficiency in wireless sensor networks has drawn ample consideration in both academia as well as in industries’ R&D. The literature of energy efficiency in wireless sensor networks (WSNs) is focused on the three layers of wireless communication, namely the physical, Medium Access Control (MAC) and network layers. Physical layer-centric energy efficiency techniques have limited capabilities due to hardware designs and size considerations. Network layer-centric energy efficiency approaches have been constrained, in view of network dynamics and available network infrastructures. However, energy efficiency at the MAC layer requires a traffic cooperative transmission control. In this context, this paper presents a one-dimensional discrete-time Markov chain analytical model of the Timeout Medium Access Control (T-MAC) protocol. Specifically, an analytical model is derived for T-MAC focusing on an analysis of service delay, throughput, energy consumption and power efficiency under unsaturated traffic conditions. The service delay model calculates the average service delay using the adaptive sleep wakeup schedules. The component models include a queuing theory-based throughput analysis model, a cycle probability-based analytical model for computing the probabilities of a successful transmission, collision, and the idle state of a sensor, as well as an energy consumption model for the sensor’s life cycle. A fair performance assessment of the proposed T-MAC analytical model attests to the energy efficiency of the model when compared to that of state-of-the-art techniques, in terms of better power saving, a higher throughput and a lower energy consumption under various traffic loads

Performance enhancement of wireless communication systems through QoS optimisation

Providing quality of service (QoS) in a communication network is essential but challenging, especially when the complexities of wireless and mobile networks are added. The issues of how to achieve the intended performances, such as reliability and efficiency, at the minimal resource cost for wireless communications and networking have not been fully addressed. In this dissertation, we have investigated different data transmission schemes in different wireless communication systems such as wireless sensor network, device-to-device communications and vehicular networks. We have focused on cooperative communications through relaying and proposed a method to maximise the QoS performance by finding optimum transmission schemes. Furthermore, the performance trade-offs that we have identified show that both cooperative and non-cooperative transmission schemes could have advantages as well as disadvantages in offering QoS. In the analytical approach, we have derived the closed-form expressions of the outage probability, throughput and energy efficiency for different transmission schemes in wireless and mobile networks, in addition to applying other QoS metrics such as packet delivery ratio, packet loss rate and average end-to-end delay. We have shown that multi-hop relaying through cooperative communications can outperform non-cooperative transmission schemes in many cases. Furthermore, we have also analysed the optimum required transmission power for different transmission ranges to obtain the maximum energy efficiency or maximum achievable data rate with the minimum outage probability and bit error rate in cellular network. The proposed analytical and modelling approaches are used in wireless sensor networks, device-to-device communications and vehicular networks. The results generated have suggested an adaptive transmission strategy where the system can decide when and how each of transmission schemes should be adopted to achieve the best performance in varied conditions. In addition, the system can also choose proper transmitting power levels under the changing transmission distance to increase and maintain the network reliability and system efficiency accordingly. Consequently, these functions will lead to the optimized QoS in a given network