Abstract: Due to the dramatic growth in the use of Wireless Sensor Network (WSN) applications -- ranging from environment and habitat monitoring to tracking and surveillance, network research in WSN protocols has been very active in the last decade. With battery-powered sensors operating in unattended environments, energy conservation becomes the key technique for improving WSN lifetimes. WSN Medium Access Control (MAC) protocols address energy awareness and reduced duty cycles since the radio is the component that consumes most of the energy. This thesis investigates the performance of two recently published energy-aware MAC protocols, Crankshaft and SCP-MAC. Crankshaft has been shown to be one of the best protocols in terms of energy consumption in dense WSNs while SCP-MAC has a dedicated low duty cycle and low average latencies. The focus of this investigation is to discover techniques for reducing the latency of Crankshaft. Using OMNeT++, an open source and component-based simulation framework, this study investigates possible modifications to Crankshaft to improve its latency. The potential improvements considered include modifications to Crankshaft's retransmission contention scheme (Sift), adjustments to its inherent settings, and investigating the impact of ACKs. Since OMNeT++ readily provided only a variant of SCP-MAC identified as SCP-MAC*, the simulations results presented involve comparing variants of both protocols (Crankshaft and SCP-MAC*). The performance of these protocols is also analyzed using distinct sensor node communication patterns. It was determined that Crankshaft's latency depends on its ACK/Retransmission settings. Specifically, Crankshaft has the best latency with No ACKs, without much loss in energy consumption. But the latency can also be improved when ACKs are enabled by reducing the number of retries. Furthermore, the latency and delivery ratio are also directly governed by the WSN traffic pattern and the congestion in the network, as there was a noticeable improvement for both parameters in one-hop traffic, compared to multi-hop convergecast traffic to the sink. Finally, it was observed that Crankshaft's broadcast performance in flooding traffic can be improved by increasing the number of broadcast slots used, though this is detrimental to its performance in unicast traffic.

This book provides comprehensive coverage of the major aspects in designing, implementing, and deploying wireless sensor networks by discussing present research on WSNs and their applications in various disciplines. It familiarizes readers with the current state of WSNs and how such networks can be improved to achieve effectiveness and efficiency. It starts with a detailed introduction of wireless sensor networks and their applications and proceeds with layered architecture of WSNs. It also addresses prominent issues such as mobility, heterogeneity, fault-tolerance, intermittent connectivity, and cross layer optimization along with a number of existing solutions to stimulate future research.

Wireless Sensor Network (WSN) consists of numerous physically distributed autonomous devices used for sensing and monitoring the physical and/or environmental conditions. A WSN uses a gateway that provides wireless connectivity to the wired world as well as distributed networks. There are many open problems related to Ad-Hoc networks and its applications. Looking at the expansion of the cellular infrastructure, Ad-Hoc network may be acting as the basis of the 4th generation wireless technology with the new paradigm of ‘anytime, anywhere communications’. To realize this, the real challenge would be the security, authorization and management issues of the large scale WSNs. This book is an edited volume in the broad area of WSNs. The book covers various chapters like Multi-Channel Wireless Sensor Networks, its Coverage, Connectivity as well as Deployment. It covers comparison of various communication protocols and algorithms such as MANNET, ODMRP and ADMR Protocols for Ad hoc Multicasting, Location Based Coordinated Routing Protocol and other Token based group local mutual exclusion Algorithms. The book also covers a chapter on Extended Ad hoc On-Demand Distance Vector (EAODV) routing protocol based on Distributed Minimum Transmission Multicast Routing (DMTMR). One chapter is dedicated to OCDMA and its future application and another chapter covers development of Home Automation System using SWN.

In the Wireless Multimedia Sensor Networks (WMSNs) field, highly saturated flow increases the probability of collision and congestion in data transmission which dramatically degrade the performance of Quality of Service (QoS). Multi-channels deployment technique is often applied to parallel transmission for QoS guarantee. However, how to make trade-off between QoS requirement and energy efficiency is a challenges to energy-constrained WMSNs. Theoretical analysis of MAC layer and PHY layer structure based on IEEE 802.15.4 standard, aim to study on the cross-layer analytical model in order to provide stronger understanding on the relationship between sensor network parameters and performance, pave the way for new enhancements in succedent multi-channel optimization research. Find effective performance indicator and design efficient performance collection or estimation approach based on the corresponding metrics, which could be used as the parameter input of multi-channel assignment mechanism. Comprehensive dynamically control system is designed for multi-channel assignment task based on light weight and high efficient computation intelligence techniques. We present a fuzzy-based dynamic bandwidth multi-channel assignment mechanism (MCDB_FLS). Cross-layer proactive available bandwidth is estimated as parameters for multi-channel deployment admission control. Reinforcement learning-based approach is proposed for more wisely decision-making in multi- channel allocation mission. Furthermore, fuzzy logic-based bandwidth threshold model provides dynamic optimization on system admission control. Simulations show the MCDB_FLS performs better than benchmark on the metrics of QoS and energy efficiency, achieves the trade-off between energy efficiency and QoS improvement. Finally, we introduce the integration of incremental machine learning approach into multi-channel assignment mechanism with Deep Q Network reinforcement learning method (DQMC). Besides, fully action weight initialization is implemented based on multi-class supervised learning classifier with stacking ensemble approach. DQMC improve the ability of self-adaptive and smart control to learn pattern from different environment of multi-tasks WMSNs.

Wireless Sensor Networks (WSNs) and the Internet of Things are facing tremendous advances both in terms of energy-efficiency as well as in the number of available applications. Consequently, there are challenges that need to be tackled for the future generation of WSNs. After giving an overview of the WSN protocols and IEEE 802.15.4 standard, this book proposes IEEE 802.15.4 Medium Access Control (MAC) sub-layer performance enhancements by employing not only RTS/CTS combined with packet concatenation but also scheduled channel poling (MC-SCP). Results have shown that the use of the RTS/CTS mechanism improves channel efficiency by decreasing the deferral time before transmitting a data packet. Furthermore, the Sensor Block Acknowledgment MAC (SBACK-MAC) protocol enables more efficiency as it allows the aggregation of several acknowledgement responses in one special Block Acknowledgment (BACK) Response packet. The throughput and delay performance have been mathematically derived under both ideal conditions (a channel environment with no transmission errors) and non-ideal conditions (with transmission errors). Simulation results successfully validate the proposed analytical models. This research reveals the importance of an appropriate design for the MAC sub-layer protocol for the desired WSN application. Depending on the mission of the WSN application, different protocols are required. Therefore, the overall performance of a WSN application certainly depends on the development and application of suitable e.g., MAC, network layer protocols.