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Software-defined networking (SDN) is a new approach to designing networks. SDN decouples and migrates network control from the hardware, which enables innovative and efficient network design and operation. The SDN-based design is well adopted in data centers and enterprises. In this paper, we state that SDN-based design is beneficial in the multihop wireless networks like wireless sensor network (WSN) and propose an architecture called SDSense. We propose a novel principled approach of SDN-based WSN design, where we decompose network functions as slow (e.g., topology control) and fast (e.g., congestion control) changing components. Furthermore, we derive a network utility maximization framework for better resource allocation. We implement SDNSense, where software enabled sensors are dynamically reconfigured to adapt to current network conditions and demonstrate that SDSense can significantly improve the network performance compared to its counterparts. [ABSTRACT FROM AUTHOR]

The “first wave” of wireless ad hoc routing protocols was heavily influenced by the routing algorithms used in wired networks. However, their overheads due to topology changes and the implicit restriction to point-to-point control messages meant that extensive effort had to be expended in “fixing” them to fit the intricacies and opportunities offered by wireless environments. In this paper, we analyze and compare the most widely used routing protocols in mobile ad hoc networks (MANETs). In particular, we consider routing and control overheads, storage requirements, and network setup costs of these protocols to see how well they fit in MANETs with nodes that have scarce resources. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the indoor localization problem, i.e., identifying the Cartesian coordinates of an object or a person under the roof. To solve this problem we consider an RF-based localization method called profiling, a two-step process, where a radio map of the monitored area is first constructed by collecting signal strength from known locations. An unknown location is then predicted using this radio map as a reference. In this paper, we first propose a K nearest neighbor (KNN) profiling-based localization method dubbed LEMON (location estimation by mining oversampled neighborhoods). It is based on a low-cost, low-power wireless devices and ensures good accuracy compared to the state-of-the-art. We then propose a variant of LEMON called combinatorial localization which exhaustively searches for the best possible set of nearest neighbors. We further define a Bayesian network model for the same localization problem. The performance of these methods is evaluated through extensive experiments in various indoor areas. We found an interesting outcome that the simple KNN-based approach can offer better localization accuracy compared to other complex localization methods. Thus we further enhance the performance of the KNN-based approach using multiple RF channels. [ABSTRACT FROM PUBLISHER]

This first edition of the Internet of Things Series of IEEE Communications Magazine comes at a time when the world is slowly rolling back from the COVID pandemic to a possible endemic. Organizations worldwide are preparing business operations for this change, anticipating that the return-to-office plan will be set in motion soon. A common denomination that has helped most organizations adapt to these changes is ICT and IoT technologies. While ICT systems provided operations resilience “at scale,” IoT technologies have become instrumental in monitoring the COVID infection spread and compliance with safety protocols. Social distancing and proximity tracking, handwashing, mask wearing, and temperature screening are few of the important COVID use cases where IoT systems have proved their ground and continue to deliver results under the prevailing circumstances. [ABSTRACT FROM AUTHOR]

We consider the problem of localized energy aware routing in mobile ad hoc networks. In localized routing algorithms, each node forwards a message based on the position of itself, its neighbors and the destination. The objective of energy aware routing algorithms is to minimize the total power for routing a message from source to destination or to maximize the total number of routing tasks that a node can perform before its battery power depletes. In this paper we propose new localized energy aware routing algorithms called OLEAR. The algorithms have very high packet delivery rate with low packet forwarding and battery power consumption. In addition, they ensure good energy distribution among the nodes. Finally, packets reach the destination using smaller number of hops. All these properties make our algorithm suitable for routing in any energy constrained environment. We compare the performance of our algorithms with other existing energy and non-energy aware localized algorithms. Simulation experiments show that our algorithms present comparable energy consumption and distribution to other energy aware algorithms and better packet delivery rate. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]