Wireless sensor network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analyzed from a quality of service (QoS) perspective including three common objectives, those of energy efficiency, reliable communication and latency awareness. This review reveals that QoS aware clustering demands more attention. Furthermore, there is a need to clarify how to improve quality of user experience (QoE) through clustering. Understanding the users’ requirements is critical in intelligent systems for the purpose of enabling the ability of supporting diverse scenarios. User awareness or user oriented design is one remaining challenging problem in clustering. In additional, this paper discusses the potential challenges of implementing clustering schemes to Internet of Things (IoT) systems in 5G networks. We indicate that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT. As the current studies for WSNs are conducted either in homogeneous or low level heterogeneous networks, they are not ideal or even not able to function in highly dynamic IoT systems with a large range of user scenarios. Moreover, when 5G is finally realized, the problem will become more complex than that in traditional simplified WSNs. Several challenges related to applying clustering techniques to IoT in 5G environment are presented and discussed.

A Survey of Clustering Techniques in WSNs and Consideration of the Challenges of Applying Such to 5G IoT Scenarios

We consider the problem of deploying or repairing a sensor network to guarantee a specified level of multipath connectivity (k-connectivity) between all nodes. Such a guarantee simultaneously provides fault tolerance against node failures and high overall network capacity (by the max-flow min-cut theorem). We design and analyze the first algorithms that place an almost-minimum number of additional sensors to augment an existing network into a k -connected network, for any desired parameter k . Our algorithms have provable guarantees on the quality of the solution. Specifically, we prove that the number of additional sensors is within a constant factor of the absolute minimum, for any fixed k . We have implemented greedy and distributed versions of this algorithm, and demonstrate in simulation that they produce high-quality placements for the additional sensors.

/pdf/deploying-sensor-networks-with-guaranteed-fault-tolerance-4eyo6qnai6.pdf

Deploying sensor networks with guaranteed fault tolerance

Clustering became relevant in the past as a solution for the scalability problems of ad hoc networking, but, the unsuccessful application of ad hoc solutions to real scenarios, such as the projects SURAN and PRNet, decreased the interest of research community on ad hoc communications, and subsequently, on clustering algorithms. Recently, however, clustering techniques have gained renewed interest due to the emergence of cooperative communications for cellular networking. Clustering is envisaged, in this scenario, as a technique to team up nodes to support efficient data aggregation for energy saving, scalability and privacy among other benefits. Moreover, research on 5G networks also envisages a connected society, where everything and everyone will be connected under the umbrella of Internet of Everything (IoE). This novel communication paradigm has fostered new research on clustering, which has yielded novel and more advanced algorithms and applications. This article surveys the State-of-the-Art in clustering techniques and provides detailed descriptions of the basics of clustering and the latest novel ideas. Open issues, technical challenges and directions for future research are also outlined.

A survey on clustering techniques for cooperative wireless networks

Energy saving in wireless sensor networks (WSNs) is a critical problem for diversity of applications. Data aggregation between sensor nodes is huge unless a suitable sensor data ow management is adopted. Clustering the sensor nodes is considered an effective solution to this problem. Each cluster should have a controller denoted as a cluster head (CH) and a number of nodes located within its supervision area. Clustering demonstrated an effective result in forming the network into a linked hierarchy. Thus, balancing the load distribution in WSNs to make efficient use of the available energy sources and reducing the traffic transmission can be achieved. In solving this problem we need to �nd the optimal distribution of sensors and CHs; thus, we can increase the network lifetime while minimizing the energy consumption. In this paper, we propose our initial idea on providing a hybrid clustering algorithm based on K-means clustering and particle swarm optimization (PSO); named KPSO to achieve efficient energy management of WSNs. Our KPSO algorithm is compared with traditional clustering techniques such as the low energy adaptive clustering hierarchy (LEACH) protocol and K-means clustering separately.

https://journals.tubitak.gov.tr/elektrik/issues/elk-16-24-4/elk-24-4-47-1403-293.pdf

Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm

Underwater sensor networks (UWSNs) can be applied in sea resource reconnaissance, pollution monitoring and assistant navigation, etc., and have become a hot research field in wireless sensor networks. In open and complicated underwater environments, targets (events) tend to be highly dynamic and uncertain. It is important to deploy sensors to cover potential events in an optimal manner. In this paper, the underwater sensor deployment problem and its performance evaluation metrics are introduced. Furthermore, a particle swarm inspired sensor self-deployment algorithm is presented. By simulating the flying behavior of particles and introducing crowd control, the proposed algorithm can drive sensors to cover almost all the events, and make the distribution of sensors match that of events. Through extensive simulations, we demonstrate that it can solve the underwater sensor deployment problem effectively, with fast convergence rate, and amiable to distributed implementation.

https://www.mdpi.com/1424-8220/14/8/15262/pdf

Particle Swarm Inspired Underwater Sensor Self-Deployment

Sensor application requirements vary tremendously, ranging from densely deployed habitat-monitoring setup to the real-time constrained military applications. This paper presents the design of a novel self-organizing framework for SANETs (Sensor and Actuator Networks). We assume two wireless interfaces at the actuator nodes, one to communicate with sensor nodes, and the other, for the neighboring actuator nodes for fast and effective actuation process. We design a new protocol called ADP (Actuator Discovery protocol) which provides an optimal attachment for a sensor node to the nearest actuator. For the sensor-actuator coordination, the proposed ADP can guarantee ordering, synchronization and eliminates the redundancy of actions. It also renders the sensor and actuator nodes with the ability to self-organize and to exploit the spatial and temporal correlations in an efficient way. A new node-addressing scheme is proposed to make the routing more powerful especially in case of node failure and mobility.

/pdf/a-novel-self-organizing-framework-for-sanets-1ufhjp7c7b.pdf

A Novel Self Organizing Framework for SANETs

Underwater acoustic sensor networks (UASNs) consist of sensors that are deployed to perform collaborative monitoring of tasks over a given volume of water. The quality of the underwater acoustic link is highly unpredictable, since it mainly depends on fading and multipath, which are not easily modeled phenomena. This is return severely degrades the performance at higher layers such as extremely long and variable propagation delays. In addition, this variation is generally larger in horizontal links than in vertical ones. In this paper, we analyze a modulation scheme and associated receiver algorithms. This receiver design take advantage of the time reversal (phase conjugation) and properties of spread spectrum sequences known as Gold sequences. This technique improves the signal-to-noise ratio (SNR) at the receiver and reduces the bit error rate (BER). We then applied the phase conjugation to the case of network communication. We show that this approach can give almost zero BER for a 2-hop communication compared to single hop. This link layer information can be used at the network layer to formalize routing decisions. We show these improvements by means of analytical analysis and simulations.

Underwater Acoustic Sensor Networking Using Passive Phase Conjugation

Delay and energy constraints have a significant impact on the design and operation of wireless sensor-actuator networks. We cosider a wireless sensor-actuator network, consisting of large number of sensors and few actuators, in which both energy and delay are hard constraints and must be jointly optimized. Abstract In this paper, we propose that each sensor node must transmit its data to only one of the actuators. To maximize the network lifetime and attain minimum end-to-end delays, it is essential to optimally match each sensor node to an actuator and find an optimal routing scheme. We model the actuator selection and optimal flow routing as joint optimization problem, which is NP-hard in general. Therefore, we use a relaxation technique and provide a distributed solution for optimal actuator selection subject to energy and delay constraints. Further, once the destination actuators are fixed, we provide an optimal flow routing solution with the aim of maximizing network lifetime. We then propose to use a delay-energy aware TDMA based MAC protocol in compliance with the routing algorithm. The optimal routing and TDMA MAC schemes together guarantees a near-optimal lifetime. The proposal is validated by means of analysis and ns-2 simulation results.

/pdf/maximizing-network-lifetime-in-large-scale-heterogeneous-4ke4x111i0.pdf

Maximizing network-lifetime in large scale heterogeneous wireless sensor-actuator networks: a near-optimal solution

Stability and delay constraints have significant impact on the design and operation of wireless sensor networks. In this paper, we propose a closed architecture for data sampling in wireless sensor networks. Examples show that the proposed scheme outperforms the traditional layered scheme, both in terms of stable operating region as well as the end-to-end delays. We then propose a distributed routing scheme for a broad class of wireless sensor networks which converges (in the Cesaro sense) to the set of Cesaro-Wardrop equilibria. The scheme is based on multiple time-scale stochastic approximation algorithms. Convergence is established using standard results from the related literature and validated by simulation results. Our algorithm can adapt to changes in the network traffic and delays.

/pdf/a-distributed-algorithm-to-achieve-cesaro-wardrop-1jel609c56.pdf

A Distributed Algorithm to Achieve Cesaro-Wardrop Equilibrium in Wireless Sensor Networks

Distributed systems based on networked sensors and actuators with embedded computation capabilities are commonly used to monitor and control the physical world. To provide a meaningful service such as disaster and emergency surveillance, meeting real-time-and-energy constraints and the stability of transmit queues are the basic requirements of communication protocols in such networks. In settings with sparse distribution of actuator nodes, multi-hop routing is traditionally used to relay information to a remote sink. A problem with this approach is that the loss of connectivity of actuator nodes may lead to partitioning of the network. In this paper, we address the problem of minimizing power consumption at each actuator node and minimizing assignment overhead at each sensor node while ensuring network connectivity. We propose that each actuator is enabled with two wireless interfaces: one to communicate with its assigned sensor network, and the other to communicate with the network of neighboring actuators. At any instant of time, an actuator can adjust its transmit power level to ensure connectivity and pro-actively inform its attached sensor network in case of mobility. These strategies have an associated cost. We show in this paper that at any instant of time, the strategy chosen by an actuator to adjust power and control-overhead due to mobility are optimal subject to constraints. The proposal is validated by means of analysis and simulations.

Muhammad Farukh Munir

Papers

A Novel Self Organizing Framework for SANETs

Underwater Acoustic Sensor Networking Using Passive Phase Conjugation

Maximizing network-lifetime in large scale heterogeneous wireless sensor-actuator networks: a near-optimal solution

A Distributed Algorithm to Achieve Cesaro-Wardrop Equilibrium in Wireless Sensor Networks

Increasing Connectivity in Wireless Sensor-Actuator Networks Using Dynamic Actuator Cooperation