Heterogeneous Wireless Sensor Research Articles

Steady-State Availability Evaluation for Heterogeneous Edge Computing-Enabled WSNs with Malware Infections

To evaluate the steady-state availability of heterogeneous edge computing-enabled wireless sensor networks (HECWSNs) with malware infections, we first propose a Stackelberg attack-defence game to predict the optimal strategies of malware and intrusion detection systems (IDSs) deployed in heterogeneous sensor nodes (HSNs). Next, we present a new malware infection model—heterogeneous susceptible-threatened-active-recovered-dead (HSTARD) based on epidemic theory. Then, considering the heterogeneity of sink sensor nodes and common sensor nodes and the malware attack correlation, we derive the state transition probability matrix of an HSN based on a semi-Markov process (SMP), as well as the steady-state availability of an HSN. Furthermore, based on a data flow analysis of HSNs, we deduce the steady-state availability of HECWSNs with various topologies, including the star topology, cluster topology, and mesh topology. Finally, numerical analyses illustrate the influence of the IDS parameters on the optimal infection probability of malware and reveal the effect of multiple factors on the steady-state availability of HSNs, including the initial infection rate, the infection change rate, and the malware attack correlation. In addition, we present data analyses of the steady-state availability of HECWSNs with various topologies, including the star topology, cluster topology, and mesh topology, which provide a theoretical basis for the design, deployment, and maintenance of high-availability HECWSNs.

Геометрические диграфы как модели гетерогенных компьютерных сетей

New mathematical models of networks are considered — geometrical oriented graphs. Such models adequately reflect the structure of heterogeneous wireless computer, sensor and other networks. The strongly connected components of geometric digraphs, their dependence on the number of network nodes in a given area, on the distributions of the radii of the zones of reception and transmission of signals are investigated. The probabilistic characteristics of random geometric digraphs, the features of the dependences of the probability of strong connectivity on the number of nodes in the digraphs for various combinations of radii are analyzed.

NovaGenesis Applied to Information-Centric, Service-Defined, Trustable IoT/WSAN Control Plane and Spectrum Management.

We integrate, for the first time in the literature, the following ingredients to deal with emerging dynamic spectrum management (DSM) problem in heterogeneous wireless sensors and actuators networks (WSANs), Internet of things (IoT) and Wi-Fi: (i) named-based routing to provide provenance and location-independent access to control plane; (ii) temporary storage of control data for efficient and cohesive control dissemination, as well as asynchronous communication between software-controllers and devices; (iii) contract-based control to improve trust-ability of actions; (iv) service-defined configuration of wireless devices, approximating their configurations to real services needs. The work is implemented using NovaGenesis architecture and a proof-of-concept is evaluated in a real scenario, demonstrating our approach to automate radio frequency channel optimization in Wi-Fi and IEEE 802.15.4 networks in the 2.4 GHz bands. An integrated cognitive radio system provides the dual-mode best channel indications for novel DSM services in NovaGenesis. By reconfiguring Wi-Fi/IoT devices to best channels, the proposed solution more than doubles the network throughput, when compared to the case of mutual interference. Therefore, environments equipped with the proposal provide enhanced performance to their users.

A parallel team formation approach using crowd intelligence from social network

– In the recent year, with the emergence of various smart devices, the data is explosively increasing in the social Internet of Things (IoT) such as human healthcare. These data mainly involve information about user behaviors collected from various heterogeneous wireless sensor and social networks. Therefore, it is vital to analyze the data to find hidden meaning and convert it into valuable information. Due to the lack of capability to handle a wide range of queries, a traditional relational database provides inefficient analysis for the data. A graph database can easily store and analyze the data from various heterogeneous wireless sensor and social network using team formation algorithm. In the healthcare field, it is important to form a team that manages patients' health efficiently. The final goal of team formation is to organize experts who can perform task of data analysis. However, the existing team formation algorithms rely on a centralized computing environment and require high communication cost among experts to form a team. In this paper, we propose a parallel team formation method on apache spark (PTFS) to analyze graph data considering the crowd intelligence capability that exists in the graph data and social network. The PTFS employs two computation stages - a find skill and a merger subgraph and provides the parallel execution of many map tasks of graph data analysis. The experimental evaluation of the proposed method on a graph dataset demonstrates that it minimizes the communicating cost of the team members to form an optimized expert team in which a desired skill set is assigned to accomplish the graph data analysis.

Spider monkey optimisation based energy efficient clustering in heterogeneous underwater wireless sensor networks

Multi-hop propagation is not viable in Underwater Wireless Sensor Network that uses acoustic signals. It causes more energy drainage of the network nodes due to longer delays in signal propagation. Also, UWSN is prone to dynamic topology changes due to node mobility caused by water current. It leads to transmission errors, link loss, collisions and congestion, if not well handled. A clustering approach based on spider monkey optimisation (SMO) is proposed here that addresses these issues. The proposed approach is found to enhance the average network lifetime of nodes by 0.01579 J and achieves a network gain of 1.35%. Further a significant reduction in average delay of messaging packets by 19.82% is achieved. The proposed approach is far more optimised as it reduces the average hops between sender and receiver by 20%.

Area k-Coverage Optimization Protocol for Heterogeneous Dense Wireless Sensor Networks

Detecting redundant nodes and scheduling their activity is mandatory to prolong the lifetime of a densely-deployed wireless sensor network. Provided that the redundancy check and the scheduling phases both help to preserve the coverage ratio and guarantee energy efficiency. However, most of the solutions usually proposed in the literature, tend to allocate a large number of unnecessary neighbor (re)discovery time slots in the dutycycle of the active nodes. Such a shortcoming is detrimental to battery power conservation. In this paper, we propose a crossing points-based heuristic to fast detect redundant nodes even in heterogeneous networks; then, an integer linear program and a local exclusion based strategy to respectively, formulate and solve the sensing unit scheduling problem. Simulations show that the resulting localized asynchronous protocol outperforms some state-of-the-art solutions with respect to coverage preservation and network lifetime enhancement.

Approximation for minimum strongly connected dominating and absorbing set with routing-cost constraint in disk digraphs

The strongly connected dominating and absorbing set (DAS) is used as a virtual backbone in heterogeneous wireless sensor. To reduce routing cost, we introduce a routing-cost constraint and study the problem of computing the minimum strongly connected DAS under routing-cost constraint. An approximation algorithm with guaranteed performance will be presented.

Research on Optimal Strategy of HWSN Coverage Based on Force-Directed Differential Evolution Algorithm

A dynamic sensor deployment strategy for heterogeneous mobile wireless sensor networks is proposed, so-called virtual force-directed differential evolution algorithm (VFDE). To ensure efficient coverage of networks, VFDE combines the virtual force (VF) with differential evolution algorithm (DE), where the position vector of each population is updated according to not only the historical local and global optimal solutions but also the virtual forces of sensor nodes. The key motivation of this strategy is to use the virtual force to direct the updating of DE for improving the convergence speed, and DE is used to enhance the global searching ability. Simulation results show that VFDE has better performance on regional convergence and global searching than VF algorithm and DE algorithm, and it can implement dynamic heterogeneous mobile sensor deployment efficiently and rapidly.

E±cient and Dynamic Clustering Scheme for Heterogeneous Multi-level Wireless Sensor Networks

E±cient and Dynamic Clustering Scheme for Heterogeneous Multi-level Wireless Sensor Networks

Study of QoS for Heterogeneous Wireless Multimedia Sensor Networks

Study of QoS for Heterogeneous Wireless Multimedia Sensor Networks

A complete hierarchical key management scheme for heterogeneous wireless sensor networks.

Heterogeneous cluster-based wireless sensor networks (WSN) attracted increasing attention recently. Obviously, the clustering makes the entire networks hierarchical; thus, several kinds of keys are required for hierarchical network topology. However, most existing key management schemes for it place more emphasis on pairwise key management schemes or key predistribution schemes and neglect the property of hierarchy. In this paper, we propose a complete hierarchical key management scheme which only utilizes symmetric cryptographic algorithms and low cost operations for heterogeneous cluster-based WSN. Our scheme considers four kinds of keys, which are an individual key, a cluster key, a master key, and pairwise keys, for each sensor node. Finally, the analysis and experiments demonstrate that the proposed scheme is secure and efficient; thus, it is suitable for heterogeneous cluster-based WSN.

Hybrid Wired and Wireless Sensor Networks Interconnection

This paper proposes a integration scheme for heterogeneous wired and wireless sensor networks. In the scheme, a complete solution is provided, in order to achieve enhanced flexibility, efficiency, and performance for the overall networked system. In addition, the hybrid networks integration scheme is able to combine the advantages of both wired and wireless solutions. From the theoretical and simulative perspectives, the paper analyzes the performance parameters, including the cost, the delay time and packet loss rate, and the analytical results show that the performance of the scheme is better than other interconnection techniques.

ISENSE: Intelligent Sensor Monitoring Services with Integrated WSN Testbed

Wireless sensor network (WSN) is drawing interest in various areas as they have great potential for many distributed applications in different scenarios. This paper demonstrates iSENSE, which provides a web-based sensor monitoring service and a sensor network test-bed. iSENSE uses heterogeneous wireless sensors that are capable of measuring temperature, humidity and light. Gateway nodes collect the sensed data from their respective network area and store the data in MySQL database for analysis and visualization through a portal. Through the test-bed user can remotely submit a sensor application (programs written in NesC) for compiling it using required softwares (TinyOS and NesC) and evaluating the performance of the application by downloading and executing them on dedicated sensing devices which form the test-bed.

A Task Scheduling Strategy in Heterogeneous Multi-sinks Wireless Sensor Networks

Using multiple sinks in a wireless sensor network can significantly decrease the amount of energy spent on communication, so it has been paid much attention in recent years. In this paper, we introduce a new divisible load scheduling strategy to solve the problem how to complete the tasks within the possibly shortest time in multi-sinks wireless sensor network. In this strategy, the tasks are distributed to wireless sensor network based on the processing and communication capacity of each sensors by multiple sinks. After received the sub-tasks, the intra-cluster sensors perform its tasks simultaneously, and send its results to cluster head sequentially. By removing communications interference between each sensor, reduced makespan and improved network resource utilization achieved. Cluster heads send fused data to sinks sequentially after fused the data got from intra-cluster sensors, which could overlap the task-performing and communication phase much better. A unique scheduling strategy that allows one to obtain closed form solutions for the optimal finish time and load allocation for each node in heterogeneous clustered networks is presented. And solutions for an optimal allocation of fractions of task to sensors in the network are also obtained via bi-level programming. Finally, simulation results indicate this strategy reasonably distributes tasks to each node in multi-sinks wireless sensor networks, and effectively reduces the time-consuming of task completion. Compared to the traditional single-sink structure, makespan is reduced by 20%, and the energy-consuming of sensors is more balanced.

An Effective Data Gathering Scheme in Heterogeneous Energy Wireless Sensor Networks

Abstract Data gathering is a major function of many applications in wireless sensor networks (WSNs). In real-world applications, it is unrealistic to guarantee that all sensors have the same lifetime because they have different energy consumption. Moreover, sensor redeployment also results in the heterogeneous energy capacities. In this paper, an Effective Data GAthering (EDGA) scheme for heterogeneous energy WSNs is proposed. Based on weighted election probabilities of each node’s energy, EDGA selects nodes to become cluster head, which can handle better the heterogeneous energy capacities. Moreover, EDGA adopts a simple but efficient method to solve the area coverage problem in a cluster range, namely intra-cluster coverage. Finally, the collected data are forwarded to the sink node via the routing tree. EDGA is capable of achieving a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load. The simulation results demonstrate that...

Energy-Efficient Area Coverage in Heterogeneous Energy Wireless Sensor Networks

Sensing coverage and energy consumption are two primary issues in wireless sensor networks. Sensing coverage is closely related to network energy consumption. The performance of a sensor network depends to a large extent on the sensing coverage, and its lifetime is determined by its energy consumption. In this paper, an energy-efficient Area Coverage protocol for Heterogeneous Energy sensor networks (ACHE) is proposed. ACHE can achieve a good performance in terms of sensing area coverage, lifetime by minimizing energy consumption for control overhead, and balancing the energy load among all nodes. Adopting the hierarchical clustering idea, ACHE selects the active nodes based on the average residual energy of neighboring nodes and its own residual energy parameters. Our simulation demonstrates that ACHE not only provide the high quality of sensing coverage, but also has the good performance in the energy efficiency. In addition, ACHE can better adapt the applications with the great heterogeneous energy capacities in the sensor networks, as well as effectively reduce the control overhead.