8-1 Introduction
The main objective of this thesis is to design effective MAC, duty cycle and routing protocols for multihop Wireless Sensor Networks (WSNs). Towards this objective, chapter 6 proposed an effective CSMA-CA protocol based on Gamma distribution back-off scheme and chapter 7 proposed an effective duty cycle management scheme inspired by principle of artificial chemistry. Comprehensive assessments of the performance of these two proposals demonstrate that they can achieve the stated design goals of this thesis, i.e., reduce the end-to-end delay of packets, prolong the life time of nodes and increase the network throughput. These results are based on a simple routing scheme that distributes traffic evenly over the shortest hop count paths. However, the hop count scheme uses a sole routing criterion depending on the number of hops between the originator and final destination despite the fact that there are more important criteria that have to be considered such as the end-to-end delay and probability of lost packets. Thereby, the need to develop a more powerful routing protocol is crucial to enhance the performance of multihop WSNs and constitutes the last step in accomplishing the main objective of this thesis.
Routing in wireless sensor networks has emerged as a direct consequence of the small transmission range of sensor nodes and the requirement to deploy these networks at large scale. Although the design of a routing protocol for communication networks is a longstanding practice that has been carried out using different approaches and techniques, most of these approaches and techniques cannot be directly employed to develop a routing protocol for WSNs. The main rationale behind this is that WSNs possess unique characteristics that need special consideration, e.g., low computation and communication capabilities of sensor nodes, ad-hoc deployment of networks, dynamic changes of topology due to depletion of batteries and heterogeneous traffic patterns. Accounting for these stochastic characteristics imposes a new set of design goals for WSN routing protocols. Some of these design goals characterise the requirements of nodes, e.g., the need to minimise the computational complexity and the communication overheads of the protocol (which is required to prolong the lifetime of nodes and save the needless channel occupancy). Other design goals typify the requirements of the operational conditions e.g., maximising the scalability, and adaptively (which is required to ensure a correct operations of the protocol when the size of network is enlarged or to cope with dynamic changes of these networks). These new design
M. Baz, PhD Thesis, University of York 2014
goals lead to paradigm shifts in the design of WSN routing protocols, such as using the principles of reinforcement learning [255], bio-inspired [256] or evolutionary computing [257]. Most of these approaches employ the principles of narrow artificial intelligence [258] in which a routing protocol is designed to mimic the behaviour of mindless species. Although these approaches can provide effective routing protocols, they suffer from the key limitation that their further developments are dominated by the underlying metaphors made to mimic the behaviour of mindless species.
This chapter proposes a broader perspective for designing WSN routing protocols. It conceptualises a routing protocol as a solution of a multi-objective optimisation problem [259-260] in which each node attempts to route its packets over those paths that maintain the global optimisation for the entire network. The key advantage of the proposed perspective is that it facilitates employing a wide variety of methodologies and techniques that are proposed to solve global optimisation problem in designing a routing protocol for WSNs considering their limited resources. Furthermore, it provides a unified means to obtain deep insights into the fundamental mechanisms of the well-known existing routing protocols, which in turn enable us to highlight their main contributions and limitations and draw key conclusions about the future trends in protocol design. More importantly, this chapter exploits one of the state-of-the-art optimisation algorithms, called the Harmony Search (HS) algorithm [261,262], to develop the routing protocol. The proposed protocol mimics the thinking strategy and logic reasoning of a musician ensemble during improvisation of the most pleasing harmony. Hence our proposal protocol utilises the artificial general intelligence principle which eliminates any restrictions towards future development. Moreover, the protocol is lightweight, scalable and highly adaptive as it allows each node to infer the routing metrics from the characteristics of its neighbours and utilises the principle of spatial reasoning to guide a node to discover those areas of networks that presumably yield the optimal or near optimal paths. In additional, the routing protocol provides an error-correction mechanism that reduces the possibility of routing packets over suboptimal paths. It is of interest to note that the kernel mechanisms of the proposed protocols are to enable nodes to harvest the routing metrics from the traffic, to analyse them statistically and to infer the most promising route based on these operations without a need to overwhelm the network with control packets; while the HS algorithm has been used as an inspirational source to devise these mechanisms. The benefits of the proposed protocol are assessed from different aspects, by comparing its outcomes with two existing routing protocols, IEEE 802.15.5[112] and ANT [263] under different scenarios. These assessments are also carried out over other algorithms that were proposed in this thesis, i.e., the Gamma based back-off scheme that was proposed in chapter 6 and the duty cycle management scheme that was proposed in chapter 7. The results demonstrate that the proposed protocol is able to achieve the three stated design goals of this thesis, (i.e., increase in throughput of network, prolong the lifetime of nodes and minimise the end-to-end delay of packets) without restrictions to specific topology, traffic patterns or MAC protocols.
M. Baz, PhD Thesis, University of York 2014
The remainder of this chapter is organised as follows. Section 8-2 reveals the relationships between the routing protocols and optimisation problem, subsection 8- 2-1 presents the mathematical formulation of the routing protocol as a solution for the multi-objective optimisation problem and subsection 8-2-2 summarises the key criteria that are used to evaluate the performance of optimisation algorithms. Section 8-3 employs these evaluation criteria to explore the fundamental approaches of well- known existing routing protocols and section 8-4 highlights the main limitations of the exiting approaches and draws some conclusions about the future design trends. Section 8-5 introduces the harmony search algorithm, section 8-6 provides the underlying approaches of the proposed protocol and section 8-7 presents the pseudo- code of the protocol. Section 8-8 assesses the performance of the proposed protocol under different cases and finally section 8-9 concludes this chapter.