Heterogeneous Internet of Things (HetIoT) is an emerging research field that has strong potential to transform both our understanding of fundamental computer science principles and our future living. HetIoT is being employed in increasing number of areas, such as smart home, smart city, intelligent transportation, environmental monitoring, security systems, and advanced manufacturing. Therefore, relaying on strong application fields, HetIoT will be filled in our life and provide a variety of convenient services for our future. The network architectures of IoT are intrinsically heterogeneous, including wireless sensor network, wireless fidelity network, wireless mesh network, mobile communication network, and vehicular network. In each network unit, smart devices utilize appropriate communication methods to integrate digital information and physical objects, which provide users with new exciting applications and services. However, the complexity of application requirements, the heterogeneity of network architectures and communication technologies impose many challenges in developing robust HetIoT applications. This paper proposes a four-layer HetIoT architecture consisting of sensing, networking, cloud computing, and applications. Then, the state of the art in HetIoT research and applications have been discussed. This paper also suggests several potential solutions to address the challenges facing future HetIoT, including self-organizing, big data transmission, privacy protection, data integration and processing in large-scale HetIoT.

How Can Heterogeneous Internet of Things Build Our Future: A Survey

Wireless sensor networks (WSNs) are one of the key enabling technologies for the internet of things (IoT). WSNs play a major role in data communications in applications such as home, health care, environmental monitoring, smart grids, and transportation. WSNs are used in IoT applications and should be secured and energy efficient in order to provide highly reliable data communications. Because of the constraints of energy, memory and computational power of the WSN nodes, clustering algorithms are considered as energy efficient approaches for resource-constrained WSNs. In this paper, we present a survey of the state-of-the-art routing techniques in WSNs. We first present the most relevant previous work in routing protocols surveys then highlight our contribution. Next, we outline the background, robustness criteria, and constraints of WSNs. This is followed by a survey of different WSN routing techniques. Routing techniques are generally classified as flat, hierarchical, and location-based routing. This survey focuses on the deep analysis of WSN hierarchical routing protocols. We further classify hierarchical protocols based on their routing techniques. We carefully choose the most relevant state-of-the-art protocols in order to compare and highlight the advantages, disadvantage and performance issues of each routing technique. Finally, we conclude this survey by presenting a comprehensive survey of the recent improvements of low-energy adaptive clustering hierarchy routing protocols and a comparison of the different versions presented in the literature.

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Hierarchical routing protocols for wireless sensor network: a compressive survey

Wireless sensor networks consist of independent sensors that sense and monitor the area of deployment and distributedly communicate this information to base station. The desirables of WSN are to have long longevity and high reliability along with maximized coverage. LEACH is one of the most discussed hierarchical, cluster-based routing protocols for sensor networks owing to its load-balancing characteristics. In this paper, we have presented a hybrid approach (H-LEACH) in which the clusters are fixed, but the cluster heads are chosen dynamically. The approach shows an improved performance that is duly supported by the simulation results using MATLAB. The paper concludes with the limitations and further scope for improvement in the proposed protocol.

H-LEACH: Modified and Efficient LEACH Protocol for Hybrid Clustering Scenario in Wireless Sensor Networks

We study a heterogeneous two-tier wireless sensor network in which $N$ heterogeneous access points (APs) collect sensing data from densely distributed sensors and then forward the data to $M$ heterogeneous fusion centers (FCs). This heterogeneous node deployment problem is modeled as an optimization problem with the total power consumption of the network as its cost function. The necessary conditions of the optimal AP and FC node deployment are explored in this paper. We provide a variation of Voronoi Diagram as the optimal cell partition for this network and show that each AP should be placed between its connected FC and the geometric center of its cell partition. In addition, we propose a heterogeneous two-tier Lloyd algorithm to optimize the node deployment. Furthermore, we study the sensor deployment when the communication range is limited for sensors and APs. Simulation results show that our proposed algorithms outperform the existing clustering methods like Minimum Energy Routing, Agglomerative Clustering, Divisive Clustering, Particle Swarm Optimization, Relay Node placement in Double-tiered Wireless Sensor Networks, and Improved Relay Node Placement, on average.

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Energy-Efficient Node Deployment in Heterogeneous Two-Tier Wireless Sensor Networks With Limited Communication Range

We study a heterogeneous two-tier wireless sensor network in which N heterogeneous access points (APs) collect sensing data from densely distributed sensors and then forward the data to M heterogeneous fusion centers (FCs). This heterogeneous node deployment problem is modeled as an optimization problem with the total power consumption of the network as its cost function. The necessary conditions of the optimal AP and FC node deployment are explored in this paper. We provide a variation of Voronoi Diagram as the optimal cell partition for this network and show that each AP should be placed between its connected FC and the geometric center of its cell partition. In addition, we propose a heterogeneous two-tier Lloyd algorithm to optimize the node deployment. Furthermore, we study the sensor deployment when the communication range is limited for sensors and APs. Simulation results show that our proposed algorithms outperform the existing clustering methods like Minimum Energy Routing, Agglomerative Clustering, Divisive Clustering, Particle Swarm Optimization, Relay Node placement in Double-tiered Wireless Sensor Networks, and Improved Relay Node Placement, on average.

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Energy-Efficient Node Deployment in Heterogeneous Two-Tier Wireless Sensor Networks with Limited Communication Range

Wireless Sensor Network (WSN) is a network of sensor nodes that can sense the environment and send the information through wireless links to a sink. Wireless sensor nodes possess limited processing capability, storage and energy resources. The existence of sensor network depends on the life of sensor nodes i.e. ultimately on the energy consumption during its operation. Thus, in WSN, the efficient use of energy resources is very much necessary. Clustering is one of the approaches for energy saving in WSN. A cluster is a group of sensor nodes with one central entity named Cluster Head (CH). In this article, a new way of clustering for CH selection and cluster formation in WSNs is proposed; in which sensor network is divided into zones as per geographic locations of nodes. Clusters are formed within the zones by taking into account the residual energy of nodes and node distance. All cluster members send the sensed data to their respective CH. Hence, CH consumes more energy as it processes the collected data before forwarding it to Base Station (BS). Dropping of cluster head's residual energy below threshold value initiates cluster reformation. Performance analysis and simulation results are given with variations in number of nodes and transmission range. The obtained results show good performance of our algorithm in terms of reduced energy consumption, increased network lifetime and scalability of the network.

Minimization of average energy consumption to prolong lifetime of Wireless Sensor Network

In wireless sensor networks (WSN) there is a need to have self-formation capabilities into an existing variety of composite computing systems. In view of the fact that functionality is distributed over a number of components in a remote area, it would be an undefeatable task to accumulate and instruct each of them individually. All network entities should behave in a self-organized manner that means the global behavior emerges through their operation on local information and direct and/or indirect mutual interaction. Based on the all characteristics, we propose architecture of self-organizing wireless sensor networks (SOWSN). The motivation to develop this model is multifold. There is need to study various parameters of system that are required by the WSN to be self-organized. Hence we have come up with a model that forms a base for self-organization of WSN. This model provides ability to recognize and study significant parameters of a system along with its essential metrics.

Self-Organization Architecture and Model for Wireless Sensor Networks

Self-Organized Wireless Sensor Network (SOWSN) is a system of sensor nodes that takes global decisions through local interactions without involvement of any central entity. Wireless sensor nodes have constrained processing capability and energy. The key characteristic used to evaluate performance of Wireless Sensor Network (WSN) is its lifetime which depends on residual energy of nodes; hence the major challenge in WSN is the efficient use of available energy. Node clustering saves energy and also shows self-organization because global decision like Cluster Head (CH) selection is taken through mutual communication between nodes. In this paper, a new clustering method based on self-organization is implemented to boost lifetime of WSN. Sensor network is divided into regions. Cluster formation relies on Residual Energy (RE) and nearest Distance (D) from CH. Node with highest residual energy becomes CH. Rest nodes join the nearest CH. Clusters are broken when residual energy of CH falls below threshold energy; causing the sensor network to get self-organized into new clusters. RED also focuses to solve the energy hole problem caused due to higher energy consumption by CHs near Sink Node or Base Station (BS).

Abhishek Chunawale

Papers

Minimization of average energy consumption to prolong lifetime of Wireless Sensor Network

Self-Organization Architecture and Model for Wireless Sensor Networks

RED: Residual Energy and Distance Based Clustering to Avoid Energy Hole Problem in Self-organized Wireless Sensor Networks