Providing End-to-End Delay Guarantees for Multi-hop Wireless Sensor Networks over Unreliable Channels

Wireless sensor networks have been increasingly used for real-time surveillance over large areas. In such applications, it is important to support end-to-end delay constraints for packet deliveries even when the corresponding flows require multi-hop transmissions. In addition to delay constraints, each flow of real-time surveillance may require some guarantees on throughput of packets that meet the delay constraints. Further, as wireless sensor networks are usually deployed in challenging environments, it is important to specifically consider the effects of unreliable wireless transmissions. In this paper, we study the problem of providing end-to-end delay guarantees for multi-hop wireless networks. We propose a model that jointly considers the end-to-end delay constraints and throughput requirements of flows, the need for multi-hop transmissions, and the unreliable nature of wireless transmissions. We develop a framework for designing feasibility-optimal policies. We then demonstrate the utility of this framework by considering two types of systems: one where sensors are equipped with full-duplex radios, and the other where sensors are equipped with half-duplex radios. When sensors are equipped with full-duplex radios, we propose an online distributed scheduling policy and proves the policy is feasibility-optimal. We also provide a heuristic for systems where sensors are equipped with half-duplex radios. We show that this heuristic is still feasibility-optimal for some topologies

Efficient MAC Adaptive Protocol on Wireless Sensor Network

Wireless Sensor Networks (WSNs) have attracted a lot of attention from the research community and industry in recent years. WSNs maintenance associated with battery replacement can increase system operating costs, especially for wireless sensor networks located in hard-to-reach and dangerous places. In this study, an adaptive Medium Access Control (MAC) is proposed that can regulate the period of data acquisition and transmission. In contrast to conventional MAC, the applied adaptive MAC regulates the data transmission period based on the estimated energy use in the previous cycle. This study focuses on comparing energy efficiency between conventional and adaptive MAC. Energy usage information is retrieved directly on the sensor node. In star topology, the proposed MAC can increase the lifetime of the sensor network up to 6.67% in a star topology. In the hierarchical topology, the proposed MAC can increase network energy efficiency up to 9.17%. The resulting increase in network throughput is 17.73% for the Star network and 33.81% for the Hierarchy network. The star topology without implementing adaptive MAC has the lowest throughput of 0.188 kb/s. The highest throughput is achieved by a hierarchical topology that applies MAC with a throughput of 2.157 kb/s

QoS-Aware Joint Access Control and Duty Cycle Control for Machine-to-Machine Communications

Massive devices and various applications imposes new challenges for Machine-to-Machine (M2M) communications to enable Internet of Things (IoT). In this paper, we investigate a QoS-aware joint access control and duty cycle control problem for M2M communications to optimise the overall network performance, including energy efficiency, end-to-end delay, reliability, throughput and fairness. We first model a practical hybrid M2M communication network and measure the overall network performance through a cost function. Then, an optimisation problem is formulated to minimise the long-term aggregated network cost. Further more, we overcome the non-convexity of the cost function and mathematically derive the optimal access control. Finally, we propose a distributed access control followed by a reinforcement learning (RL) based duty cycle control which adapts to various network dynamics without priori network information. Simulation results show that, the proposed joint access control and duty cycle control minimise the network long-term aggregated cost, while achieving fairness among cluster heads with QoS differentiation

Dynamic duty cycle mechnism for mobility in wirless sensor networks

Appeared in previous years to connect the physical environments with the digital world Wireless sensing networks (WSN). There are several small sensor units through which small devices are created in which WSN is configured and can sense the physical environment properties such as heat, pressure, light, soil formation, location, and others. Physical environment properties. Through receivers and transmitters, the sensor nodes send the data hop by hopto the sink node or base station, and these devices have a short-range and a very low frequency. Through a very precise complement, the sensors are small size but at the same time contain sensors as well as radio transmitters and receivers with microprocessors that can implement local data processing that done as well as operate networks using. Besides,through a wireless medium that has been Sensing the data of the wireless transceiver in the process of transmitting and receiving data that will take place in the network.The increased demand for mobility within different applications raises the increasing question about power consumption and how to reduce itin nodes of the WSN. An example of these applications is the application of environmental monitoring, medical observation, and automation of home and this is why wireless sensor networks (WSN) usually consist of a fixed node. The aim of this project is to design a dynamic duty cycle mechanism for mobility as well as fixed nodes within wireless sensor networks through a Contiki simulator through which power consumption, Packet Delivery Ratio (PDR) and duty cycle aremeasured by nodes under the mobility and fixed condition. Done through two diverse scenarios that are the sink and the sensor nodes fixed, and the sink nodes and the nodes are the mobility that occurs. We analyze the performance of the mechanism that will be produced by Contiki on three different measures: Excel extracts PDR, power consumption and duty cycle, to reduce power consumption and these percentages

Efficient MAC Adaptive Protocol on Wireless Sensor Network

Wireless Sensor Networks (WSNs) have attracted a lot of attention from the research community and industry in recent years. WSNs maintenance associated with battery replacement can increase system operating costs, especially for wireless sensor networks located in hard-to-reach and dangerous places. In this study, an adaptive Medium Access Control (MAC) is proposed that can regulate the period of data acquisition and transmission. In contrast to conventional MAC, the applied adaptive MAC regulates the data transmission period based on the estimated energy use in the previous cycle. This study focuses on comparing energy efficiency between conventional and adaptive MAC. Energy usage information is retrieved directly on the sensor node. In star topology, the proposed MAC can increase the lifetime of the sensor network up to 6.67% in a star topology. In the hierarchical topology, the proposed MAC can increase network energy efficiency up to 9.17%. The resulting increase in network throughput is 17.73% for the Star network and 33.81% for the Hierarchy network. The star topology without implementing adaptive MAC has the lowest throughput of 0.188 kb/s. The highest throughput is achieved by a hierarchical topology that applies MAC with a throughput of 2.157 kb/s

CHOP: Maximum Coverage Optimization and Resolve Hole Healing Problem using Sleep and Wake-up Technique for WSN

The Sensor Nodes (SN) play an important role in various hazardous applications environments such as military surveillance, forests, battlefield, etc. The Wireless Sensor Network (WSN) comprised multiple numbers of sensor nodes which are used to perform sensing the physical conditions and subsequently transmitting data to the Base Station (BS). The nodes have limited batteries. The random distribution of nodes in the hazardous areas causes overlapping of nodes and coverage hole issues in the network. The Coverage Optimization and Resolve Hole Healing (CHOP) Protocol is proposed to optimize the network's overlapping and resolve the coverage hole problem. The working phases of the proposed protocol are network initialization, formation of the cluster, Selection of Cluster Head, and sleep and wake-up phase. The issues are optimized, and maximum coverage is achieved for a specific sensing range. Using statistics and probability theory, a link is established between the radius of the node and the coverage area. The protocol used the sleep and wake phase to select optimal nodes active to achieve maximum coverage. The proposed protocol outperformed and showed improvements in the network's performance and lifetime compared to LEACH, TEEN, SEP, and DEEC protocols

LB-MAC: A Lifetime-Balanced MAC Protocol for Sensor Networks

Abstract. This paper presents LB-MAC, a new MAC protocol for asyn-chronous, duty cycle sensor networks. Different from existing sensor network MAC protocols that usually focus on reducing energy consump-tion and extending lifetime of individual sensor nodes, LB-MAC aims at prolonging the network lifetime through balancing the nodal lifetime between neighboring sensors. LB-MAC is lightweight and scalable as the required control information is only exchanged locally between neighbors. LB-MAC has been implemented in TinyOS and evaluated on a sensor network testbed with extensive experiments. Results show that LB-MAC is able to achieve a significantly longer network lifetime than state-of-the-art MAC protocols such as X-MAC, RI-MAC and SEESAW, while maintaining comparable levels of network power consumption, packet delay and delivery ratio.