Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications

In recent years, the networks of low-power devices have gained popularity. Typically these devices are wireless and interact to form large networks such as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable Computing, and Wireless Sensor Networks. The collaboration among these devices is a key to achieving the full potential of these networks. A major problem in this field is to guarantee robust communication between elements while keeping the whole network energy efficient. In this paper, we introduce an extended and improved emergent broadcast slot (EBS) scheme, which facilitates collaboration for robust communication and is energy efficient. In the EBS, nodes communication unit remains in sleeping mode and are awake just to communicate. The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up window in partially overlapped manner within each duty-cycle to avoid message collisions. We show the theoretical convergence behavior of the scheme, which is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa

Fast Desynchronization For Decentralized Multichannel Medium Access Control

Distributed desynchronization algorithms are key to wireless sensor networks as they allow for medium access control in a decentralized manner. In this paper, we view desynchronization primitives as iterative methods that solve optimization problems. In particular, by formalizing a well established desynchronization algorithm as a gradient descent method, we establish novel upper bounds on the number of iterations required to reach convergence. Moreover, by using Nesterov's accelerated gradient method, we propose a novel desynchronization primitive that provides for faster convergence to the steady state. Importantly, we propose a novel algorithm that leads to decentralized time-synchronous multichannel TDMA coordination by formulating this task as an optimization problem. Our simulations and experiments on a densely-connected IEEE 802.15.4-based wireless sensor network demonstrate that our scheme provides for faster convergence to the steady state, robustness to hidden nodes, higher network throughput and comparable power dissipation with respect to the recently standardized IEEE 802.15.4e-2012 time-synchronized channel hopping (TSCH) scheme.Comment: to appear in IEEE Transactions on Communication

WisperNet: Anti-Jamming for Wireless Sensor Networks

Resilience to electromagnetic jamming and its avoidance are difficult problems. It is often both hard to distinguish malicious jamming from congestion in the broadcast regime and a challenge to conceal the activity patterns of the legitimate communication protocol from the jammer. In the context of energy-constrained wireless sensor networks, nodes are scheduled to maximize the common sleep duration and coordinate communication to extend their battery life. This results in well-defined communication patterns with possibly predictable intervals of activity that are easily detected and jammed by a statistical jammer. We present an anti-jamming protocol for sensor networks which eliminates spatio-temporal patterns of communication while maintaining coordinated and contention-free communication across the network. Our protocol, WisperNet, is time-synchronized and uses coordinated temporal randomization for slot schedules and slot durations at the link layer and adapts routes to avoid jammers in the network layer. Through analysis, simulation and experimentation we demonstrate that WisperNet reduces the efficiency of any statistical jammer to that of a random jammer, which has the lowest censorship-to-link utilization ratio. WisperNet is more energy efficient than low-power listen CSMA protocols such as B-mac and is simple to analyze in terms of effective network throughput, reliability and delay. WisperNet has been implemented on the FireFly sensor network platform

Anti-Jamming for Embedded Wireless Networks

Resilience to electromagnetic jamming and its avoidance are difficult problems. It is often both hard to distinguish malicious jamming from congestion in the broadcast regime and a challenge to conceal the activity patterns of the legitimate communication protocol from the jammer. In the context of energy-constrained wireless sensor networks, nodes are scheduled to maximize the common sleep duration and coordinate communication to extend their battery life. This results in well-defined communication patterns with possibly predictable intervals of activity that are easily detected and jammed by a statistical jammer. We present an anti-jamming protocol for sensor networks which eliminates spatio-temporal patterns of communication while maintaining coordinated and contention-free communication across the network. Our protocol, WisperNet, is time-synchronized and uses coordinated temporal randomization for slot schedules and slot durations at the link layer and adapts routes to avoid jammers in the network layer. Through analysis, simulation and experimentation we demonstrate that WisperNet reduces the efficiency of any statistical jammer to that of a random jammer, which has the lowest censorship-to-link utilization ratio. WisperNet has been implemented on the FireFly sensor network platform

An artificial intelligence based quorum system for the improvement of the lifespan of sensor networks.

Artificial Intelligence-based Quorum systems are used to solve the energy crisis in real-time wireless sensor networks. They tend to improve the coverage, connectivity, latency, and lifespan of the networks where millions of sensor nodes need to be deployed in a smart grid system. The reality is that sensors may consume more power and reduce the lifetime of the network. This paper proposes a quorum-based grid system where the number of sensors in the quorum is increased without actually increasing quorums themselves, leading to improvements in throughput and latency by 14.23%. The proposed artificial intelligence scheme reduces the network latency due to an increase in time slots over conventional algorithms previously proposed. Secondly, energy consumption is reduced by weighted load balancing, improving the network’s actual lifespan. Our experimental results show that the coverage rate is increased on an average of 11% over the conventional Coverage Contribution Area (CCA), Partial Coverage with Learning Automata (PCLA), and Probabilistic Coverage Protocol (PCP) protocols respectively