Traffic Load Minimization in Software Defined Wireless Sensor Networks

Wireless Sensor Network (WSN), which are enablers of the Internet of Things (IoT) technology, are typically used en-masse in widely physically distributed applications to monitor the dynamic conditions of the environment. They collect raw sensor data that is processed centralised. With the current traditional techniques of state-of-art WSN programmed for specific tasks, it is hard to react to any dynamic change in the conditions of the environment beyond the scope of the intended task. To solve this problem, a synergy between Software-Defined Networking (SDN) and WSN has been proposed. This paper aims to present the current status of Software-Defined Wireless Sensor Network (SDWSN) proposals and introduce the readers to the emerging research topic that combines Machine Learning (ML) and SDWSN concepts, also called ML-SDWSNs. ML-SDWSN grants an intelligent, centralised and resource-aware architecture to achieve improved network performance and solve the challenges currently found in the practical implementation of SDWSNs. This survey provides helpful information and insights to the scientific and industrial communities, and professional organisations interested in SDWSN, mainly the current state-of-art, ML techniques, and open issues.

Wireless Sensors Networks (WSNs) have been gaining significant attention in both the industries and the academia in recent years. However, WSN are vulnerable to growing security threats and attacks which are inept for the current traditional security mechanisms to cope with or mitigate such security challenges. As a solution, Software Defined Network (SDN) has emerged and been merged with WSN to form what is known as Software Defined Wireless Sensor Network (SDWSN). SDWSN is introduced to bring flexibility, programmability and innovation to the WSN network. However, SDWSN is not exempted from security challenges. SDWSN is faced with multitude of security challenges inherited from both SDN and WSN which have become a bottle-neck to its operations and applicability. Therefore, this paper presents security challenges in both WSN and SDN which are transferable to SDWSN. We discussed the inheritable security challenges from the perspective of SDN and WSN by outlining several possible threats, attacks and some countermeasures. This is important to bring together these challenges in order to attract or stimulate more research and development activities aim at realizing a more secure and dependable SDWSN.

The Software-Defined Wireless Sensor Networking (SDWSN) paradigm aims to solve inherent issues present in Wireless Sensor Networks (WSN), such as resource constraints, by adopting a Software-Defined Networking (SDN) approach to the management of these WSNs. The security aspect of SDWSN has received little attention due to a focus on the architecture. As this paradigm is a combination of both WSN and SDN, some solutions from both paradigms can be adapted to consider SDWSN. One of the main problems with implementing security within WSN, lies within its inherent issues, such as resource constraints. However, due to the centralization of control brought about by the SDN paradigm, most of these issues are alleviated, leaving room for WSN security implementations. In order to investigate the use of WSN cryptography within SDWSN, cryptography methods have been implemented within a SDWSN network in order to verify whether the SDWSN paradigm does allow for resource intense WSN security implementations.

In Wireless Sensor Network (WSN), resource optimization is one of the challenging issues. It improves the network performance. This can be achieved with the help of a new networking technology, called Software Defined Networking (SDN). The concept of SDN is to decouple the control plane from the forwarding plane of a network to improve the performance of the networking applications. Traffic Engineering (TE) is a domain of network applications that manages the network traffic, and try to optimize the network resources. SDN offers multiple features to support TE applications. SDN combined with WSN forms a new networking domain called Software Defined WSN (SDWSN). Since WSN has resource-constrained nodes, resource optimization is a need in WSN. This paper proposes an optimized link utilization based approach for TE in SDWSN. The proposed approach discusses about a traffic optimization algorithm, called Optimized Link Allocation based TE (OLA-TE). OLA-TE is implemented at the controller node and helps to improve the overall network utilization. The SDN sensor nodes find the optimized path for traffic routing with the help of controller node. The proposed approach is compared with the traditional WSN approach. IBM CPLEX Optimization Studio and MATLAB are used for validation purposes. The CPLEX results assure a network flow-cost optimization of about 10%. The results of MATLAB show that despite having extra control traffic on network, the network performance gets improved over the period of time.

The ever-growing increase in modern and ubiquitous applications of wireless sensor networks (WSNs) is causing energy scarcity, which is a serious threat to the lifetime of the network. Wireless power transfer emerges as a promising solution to replenish the sensor nodes. In wireless power transfer, energy is transferred to sensor nodes through dedicated energy transmitters. In addition, software-defined WSNs (SDWSNs) have been recently realized to fully explore and efficiently utilize the resources of WSNs. In this paper, we present an energy efficient SDWSN with wireless power transfer. We propose a mechanism to place energy transmitters and determine minimum number of energy transmitters. For placement of energy transmitters, a tradeoff between maximum energy charged in the network and fair distribution of energy is studied. We present this mechanism by defining a utility function to maximize both total energy charged and fairness. For minimum number of energy transmitters, an optimization problem is formulated and solved while satisfying the constraint on minimum energy charged by each sensor node. We also propose an energy-efficient scheduling scheme for energy transmitters for the given tasks of energy charging. The focus is to minimize the energy consumption of energy transmitters while keeping sensor nodes sufficiently charged. Finally, this paper is supported by extensive simulation results, which illustrate the performance of energy-efficient SDWSNs with wireless power transfer in terms of energy charged, fairness, number of energy transmitters, number of tasks, and energy consumption.

The paper analyses the performance of a software defined wireless sensor network (SD-WSN) to a more conventional ad-hoc wireless sensor network (WSN). Recently SD-WSN has increased in popularity due to the demand of managed and service oriented sensor networks. In this analysis, we perform several simulation experiments comparing convergence time, packet reception ratio, and data delivery time for the SDN-WISE SD-WSN system and an ad-hoc WSN based the RPL routing protocol. The experimental results confirm the expected overhead required in a SD-WSN compared to an ad-hoc approach and exposes some design flaws in the SDN-WISE architecture.

The software‐defined wireless sensor networks (SDWSNs) have been proposed recently to solve the energy limitation of sensor nodes and extend the lifetime of the wireless sensor networks by fast node reconstruction and dynamical resource allocation. In this study, the authors investigate an energy‐efficient resource allocation algorithm in SDWSNs, in which radio resource allocation could be handled at central controllers with powerful storage and computation capacity. In this algorithm, the authors formulate an optimisation problem to minimise the energy consumption, under the individual constraint of quality of service. Then, the initial optimisation problem is transformed using semidefinite relaxation, to achieve centralised adaptive bandwidth and power allocation (CABPA). Additionally, two special cases are derived to reveal the performance of the CABPA. Furthermore, an OpenFlow‐based scheme is proposed for information exchanging and updating to realise the centralised resource allocation. Meanwhile, a distributed scheme with limited information about the whole network is developed to serve as a performance benchmark for the CABPA in the SDWSN. Finally, the simulation results reveal that the proposed CABPA performs better than the other algorithms, and it balances the power and bandwidth utilisation.

The idea of software-defined wireless sensor networks (SDWSNs) have drawn a lot of attention in these years. To implement SDWSN, routing mechanism is one of the most important part. In this paper, we propose a mechanism of load-balance centralized-control routing protocol (LCCR) to establish the route of data upload. Sensor nodes report their topology information to the controller. The controller then gets the routing rules using the load-balance based algorithm. Finally, the routing rules are distributed to all sensor nodes. We have realized the LCCR on our SDWSN system. The practical test results demonstrate that LCCR performs well on reducing unstable links being chosen as one of data upload paths, which contribute to higher bandwidth and lower packet loss.

Software defined wireless sensor network (SDWSN) is a new network architecture for sensor networks. It provides an information monitoring and management technology solution for wireless sensor network, and has become a research hot spot in recent years. Despite the advantages of SDWSN, there are still some unavoidable problems such as over concentrated load and imbalanced energy consumption with the increase of network scale. To deal with the shortages of load and energy balance in SDWSN, we propose a new hierarchical subnet space based network balance algorithm. The proposed algorithm innovatively optimizes the network structure and forwarding rules of SDWSN. Fog computing is also applied to reduce packet transmission requirement, which helps to further balance load and reduce energy consumption. In our optimized network structure, the whole network is divided into several subnets and sub-controllers are selected for each subnet. Sensor data packets are collected and compressed in the sub-controller and sent to the center controller along the path consisted of sun-controllers. Simulation results show that our proposed algorithm performs better than other existed algorithms in load balancing and energy saving.

Traditional Wireless Sensor Networks (WSN) integrate the application in their sensor nodes, limiting their ability to fulfill additional functions. The application-specific nature of WSN restricts their scope and use-case. This results in the redundant deployment of other WSNs to meet various application-specific needs. To address the inflexible nature of WSN, a software-defined paradigm can aid in achieving flexibility, simplicity, management, and the ability to compute tasks concurrently. The proposed approach utilizes the characteristics of Software-Defined Wireless Sensor Networks (SDWSN) to provide energy-efficient task allocation from a basic application decomposition to task scheduling on sensor nodes while tracking latency with minimum task failure. We proposed a load-based resource allocation to balance the network energy through machine-bottleneck task scheduling to ensure minimal task failure. The simulation results demonstrate that our pro-posed method outperforms the state-of-the-art in the total energy consumption, task completion, task completion with varying node load, and percentage change in energy consumption.

This1 article introduces Software Defined Network (SDN) technology into the Wireless Sensor Network (WSN) field, the working mechanism of OPENFLOW, and the software defined wireless sensor network (SDN-WISE). The network architecture is improved, and the data plane and control plane of the WSN are decoupled. In-depth research on data processing and forwarding in the network is intensified. Based on the SDN-WISE architecture, a rule-action forwarding strategy derived from OPENFLOW is derived from the WSN. The forwarding table is stored at the starting point of the communication link. The route nodes do not need to check the table to forward data, which effectively reduces the network energy consumption. The network is simulated and tested through experiments. The simulation structure shows that the algorithm has certain advantages[1, 2].

Software-Defined Wireless Sensor Network: A Comprehensive Survey

This paper draws attention to techniques available for the minimization of control overhead in software-defined wireless sensor networks (SDWSNs). Software-defined networking (SDN) promises improved management flexibility and control for inherently resource-constrained and heterogeneous wireless sensor network (WSN) implementations. However, due to the in-band traffic channel available for data and control traffic in SDN-based WSNs, overhead control traffic has been viewed as a bottleneck affecting network performance and controller responsiveness. A discussion on the need for control message quenching (CMQ) and the various categories of CMQ implementations in SDWSN is made in this paper. Furthermore, a CMQ algorithm based on reducing duplicate flow request packets is discussed and demonstrated for implementation in an SDN-based WSN framework. Results show a significant reduction in control overhead traffic and noticeable improvement in energy efficiency. However, trade-offs in terms of packet delivery rate and packet delay are also observed as a result of the CMQ algorithm. A discussion on future work necessary to optimize CMQ algorithms in order to minimize the associated trade-offs is also made.

In this paper, one centralized resource allocation algorithm is proposed to minimize energy consumption in software defined wireless sensor networks (SD-WSNs). The energy consumption problem is formulated as an optimization problem, given quality-of-service (QoS) constraint defined as Signal-to-Interference-plus-Noise Ratio (SINR). Then, the nonconvex optimization problem is relaxed into a semidefinite programming (SDP), which serves as a lower bound. To analyze the tightness of the lower bound, two special cases are introduced. Besides, one distributed approach is also developed to provide a performance benchmark. Furthermore, simulation results are revealed that the proposed centralized algorithm performances better with respect to the energy consumption and bandwidth utilization.

Software‐defined wireless sensor networking (SDWSN) is a new wireless networking paradigm formed by applying software‐defined networking to wireless sensor networks. Fragmentation‐based distributed control system offers an efficient way of distributing the SDWSN control services across the network. Fragmentation aims to bring the control services closer to the infrastructure network in order to reduce the propagation latency. It also aims to improve the scalability, reliability, and performance of the network. The fragmentation model is earmarked to play a huge role in stimulating participation of SDWSN in Internet of Things. To realize this, we optimize the model for deployment and integration as well as for operational efficiency. We consider two aspects: controller placement and controller reelection after failure. This paper discusses the controller placement techniques suitable for SDWSN and the controller replacement in a case of failure for SDWSN. The controller placement and the controller replacement mechanism were both evaluated and the results proved to be effective and efficient.