Multi-hop Routing in Wireless Sensor Networks: An Overview, Taxonomy, and Research Challenges

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As data is carried and passed on from node to node, less energy is required and it also allows for data aggregation which reduces redundancy in the network. The challenge with this for enabling SDN-based management is the requirement for communication between the global controller and the nodes on the network as it may happen that a link may break once any of the nodes acting as repeaters falls out of the network.

A more reliable communication scheme would integrate long range radio between each of the nodes and the controller although it may be argued that such a system would be less energy efficient. One solution would be investigating the possibility of using low power long range radio schemes such as LoRa [ ]. In addition, to reduce rigidity in choice of design or communication scheme due to energy constraints for WSNs based on SDN, there is need for integration of energy harvesting mechanisms in the network.

Methods to reduce the overhead on control data such as the proposed reinforcement learning technique [ ] or a promising energy harvest method that uses wireless power transfer from a transmitting generator to the nodes in the field [ ] can be further developed and investigated to reduce the energy bottleneck that exists in WSNs. In SDN-based energy management of WSNs, implementing a mix of proposed schemes to reduce and monitor energy consumed in the network such as duty cycling, data aggregation, smart [ 14 ] and multi-task methods [ ] with energy harvesting techniques would result in higher energy efficiency of the network.

It is also worthwhile to mention here that sensor node design is also focused on minimizing the energy consumed by use of low power devices in the electronic design while meeting the required QoS. In Table 5 various SDN-based management schemes and techniques for WSNs discussed in this paper are evaluated against the design criteria required for improved management. Generally, there is significant and on going contributions in investigating SDN-based management of networks, topologies, energy, QoS and enabling technologies for WSNs.

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Journal of Network and Computer Applications D S , F is the distance between a source and forwarding node, whereas D S , S is the distance between source and the sink node, R is the maximum transmission range, and T Delay is a predefined maximum delay. Directed Diffusion Protocol for wsn Load-Balanced Clustering Algorithm Directed diffusion is a data-centric routing protocol for sensor query dissemination and processing. Your part amount should close at least 2 sources not. Learn a Filter in the based to create the name.

However, a number of open challenges still exist:. With increase in sensor nodes to hundreds or thousands, use of a single controller becomes inefficient in terms of maintaining a global network view and data collection therefore proposals have been made towards using multiple controllers to solve this issue [ 28 ].

Routing in Wireless Sensor Networks- Part- II

SDN-based management of communication protocols between distributed controllers in the control plane while maintaining a logically centralized and global view of the entire wireless sensor network remains an open challenge. This includes development of East-West bound APIs for efficient control of data flow in the data plane. Most resource management techniques available such as Smart and SDWN have the problem of not addressing overhead in control traffic which is costly for resource constrained WSNs. Therefore, further investigation on how to reduce in-band control traffic between the control and data planes is required.

Efficient techniques for in-band communication of control and data traffic can be proposed and implemented. Context based clustering can be studied further using other techniques other than HyperFlow to efficiently implement the logical controller concept while making use of its improved performance metrics such as improved scalability and reduced latency.

Aspects of network decomposition hierarchies can be looked into to minimize control traffic and improve energy efficiency. Further investigation is also required to determine the number of controllers needed and their placement given an SDN-based WSN topology similar to the analysis done in [ ] for WANs.

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SDN-based network monitoring for WSNs is an essential part of network management that still remains largely unexplored. Node localisation is another issue that has the potential to be improved by SDN, conventional WSNs may require nodes to determine their geographical location based on information from other nodes [ 5 ] thus expending more energy. This task can be moved to the controller by virtue of its global position reducing the energy consumption on the nodes. In addition, novel localization techniques can be developed harnessing the potential of SDN.

The existence of a logically centralized controller and cluster heads in the SDN-based architecture for WSNs calls for efficient management of security. This includes investigation and development of support for securing the controller in both distributed and centralized architectures in addition to counter measures whenever a cluster head or controller is attacked.

There is also an open challenge in development of SDN-based key management systems and other encryption techniques for WSNs. There is need for more investigations in the controller placement problems to improve these performance metrics. Wang et al.

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Statistical analysis and artificial intelligence to predict fault occurrence in the network are also being investigated [ 24 ] for management of a robust SDN-based WSN. Investigation on the feasibility of mobility management techniques implemented in cellular networks being used in node mobility management of WSNs based on SDN is also a worthwhile area of research. Back up techniques upon node failure such as function alternation [ 65 ] can be investigated further based on leveraging SDN to enable efficient and simpler function alternation.

Energy is a scarce resource in WSNs and constant research in this area is necessary to ensure efficient energy use in WSNs. A common technique to minimize the energy use is by control of sleep and wake states of sensor nodes however SDN-based management of WSNs requires a robust link between the control and data planes for effective management and thus should be investigated further to reduce unreliability in communication between the planes as a result.

A paradigm shift is required to move away from data aggregation and further develop efficient long range low power radio techniques such as LoRa. Low power single hop communication techniques like this can also save energy by shifting in-network processing to the controller leaving the energy deprived sensor nodes with the task of only forwarding data to the controller and going back to sleep.

Other improvements of energy efficiency based on reduction of overhead control traffic and redundancy in routing tasks are also a promising area of research. While new methods of extending network lifetime through wireless power transfer [ ] have been proposed, the feasibility of implementing such a technique in a large-scale WSN based on SDN has to be addressed in terms of the scalability-cost ratio. Advances in microelectronic design and manufacture has allowed for miniaturisation of node hardware and at a lower production cost a factor which is useful in large-scale applications and allows for placement of redundant nodes in a network.

However, there is need for continuous research in developing increased energy efficiency while keeping these nodes small and at a reduced cost. The energy harvest mechanisms is one such area of development, there is room for developing batteries that support quick and efficient charging at lower currents. A characteristic like this would be useful in harvesting solar energy for example.

Integration of these nodes into the SDN architecture will also require further development of software and hardware to enable the SDN functionality and also provide support for multiple retasking, inter-plane data exchange via APIs and communication protocols Flow-Sensor [ ], FlowVisor [ ], HyperFlow [ 93 ]. There is also need to develop some form of modularity in both software and hardware to allow for use in multiple applications and enable easy system maintenance.

In terms of choice of using FPGA, micro-controller or a hybrid of both in SDN sensor node design, it can be argued that it vastly depends on energy efficiency, cost and nature of application. There are still possibilities of integrating low power FPGAs however the cost impact for application in large-scale networks also needs to be accounted for. Generally, novel hardware and software needs to be developed to improve support for the measurement, analysis and decision making process for IoT applications such as smart water grids while allowing compatibility with the integrated management framework.

In the future, a development trend of more than just concepts and ideas of proposed management techniques is required; more work is needed for proof of concept and actual deployments to allow for a deeper understanding of the necessary architectures and tools for SDN-based management of WSNs.

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Areas such as distributed management based on distributed controllers, low power and long range SDN-based management of WSNs need investigation. The management framework can be broken down to manage various aspects of the WSN and it should also be dynamic enough to be used for various applications. The SDN paradigm has introduced flexibility and simplicity in managing wireless sensor networks, despite having different vendor specific hardware in the network. A highlight of the main real-world WSN applications and how SDN would improve the management of the applications was presented.

This paper also focused on the generic architecture of SDN-based WSNs and reviewed the management schemes available to ensure efficient functionality of the network. A review of the management classifications, namely management of the network configuration, topology, QoS, energy, security, network monitoring and enabling technologies with a further focus on SDN-enabled node hardware and software, was made.

Furthermore, an attempt to define the overall management of WSNs based on SDN as abstractions of the north, south, east-west bound architecture of SDN had been presented. A discussion and summary was presented for the various proposals and work done necessary for management of WSNs based on SDN. However, there still exists a mix of open challenges available for effective SDN-based management of WSNs and they have been discussed in this paper with an emphasis on the need for actual implementations and test beds for effective evaluation of proposals and concepts.

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Journal List Sensors Basel v. Sensors Basel. Published online May 4. Hancke , 1, 2 and Adnan M.

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Multi-hop Routing in Wireless Sensor Networks: An Overview, Taxonomy, and Research Challenges. Book · September with Reads. This brief provides an overview of recent developments in multi-hop routing protocols for Wireless Sensor An Overview, Taxonomy, and Research Challenges.

Abu-Mahfouz 3. Gerhard P. Adnan M. Kemal Akkaya, Academic Editor. Author information Article notes Copyright and License information Disclaimer. Received Mar 3; Accepted Apr This article has been cited by other articles in PMC. Keywords: wireless sensor networks, SDN-based Wireless Sensor Networks, software defined networks for sensor nodes, network management architecture, network management abstractions.

Introduction Wireless sensor networks WSNs consist of individual nodes that interact with the environment by sensing and controlling physical parameters such as temperature, pressure and volume [ 1 , 2 ].

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WSN Management Management of WSN should allow for definition of a set of functions that promote productivity and integration in an organized manner of the configuration, maintenance, operation and administration of the components and services of the WSN [ 25 ]. The MANNA architecture considers management policies for WSN services, functions and models by looking at management of WSNs in three dimensions defining functionality abstractions: WSN functionalities which include maintenance, configuration, sensor node operation Sensing, processing, communication Management levels which include application services and management of network elements node clusters, data aggregation, network connectivity.

In this paper the structure of WSN management schemes presented is based on the above protocols [ 30 ] and abstraction entities [ 25 ] however we re-categorise them according to functional relationships as follows: a. Network Configuration Management Wireless sensor network configuration management integrates network configuration, performance management and maintenance management of the sensor nodes. QoS Management Coupled with configuration management is performance management.

Energy Management Energy management through software has been proposed [ 35 ] which minimises energy consumption of each sensor node by introducing a duty cycle to periodically turn on and then send the radio portion of a node to sleep. Security Management Management of security is difficult to provide as WSNs are mainly made up of ad-hoc wireless networks with intermittent connectivity and resource limitations [ 25 , 45 ].

Maintenance Management Maintenance management as part of network management would enable higher QoS and an extended network lifetime.

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Table 1 Available WSN management systems evaluation against the design criteria. Open in a separate window. Figure 1. WSN Applications and the Need for SDN-Based Management Wireless sensor networks are able to integrate various sensing capabilities thus providing support for various real-world applications.

Environmental Applications A popular environmental application of WSNs is based on the measurement of physical parameters such as temperature, vibration, sound, chemicals and gases. Medicine and Health Care WSN application in heath care has been considered to have the potential of being beneficial to the quality of health especially for the chronically ill and elderly patients.

Military Applications In military applications WSNs can be used to detect presence of enemy or friendly forces, assessment of terrain and chemical sensing of weapons. Wireless Home Networks WSNs for home use have seen increasing demands with arising smart homes and buildings in general. Figure 2. Network Configuration Management Network configuration management is a functional area that will allow the sensor network to meet its required specification. Scalability and Localization Management The architectures reviewed so far are based on a centralized controller in a flat topology which is easy to deploy and manage.

Figure 3. Mobility Management Sensor nodes in an SDN-based WSN are susceptible to movement and this can cause variation in packet transmission and execution of tasks making it necessary to monitor and manage the movement of nodes in the network.

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