A Service-Oriented Cloud Computing Network Management Architecture for Wireless Sensor Networks

Traditional network management techniques cannot be applied to wireless sensor networks (WSNs) because of their low computing ability, their small memory space, and the limited energy of WSNs. Although WSN network management techniques have been recently proposed, these techniques lack a complete architecture and integrated design for their external interface. In addition, future WSNs may be composed of heterogeneous sensor devices and may use a large number of applications cooperatively. Traditional network management techniques will not meet the resulting requirements. Recent advances in cloud computing and in Service-Oriented Architecture (SOA) provide exciting opportunities for solving this challenge. However, current implementations of cloud computing infrastructures are often isolated from others. To better support the multi-tenancy feature of cloud computing, this paper proposes a Service-Oriented Cloud Computing Network Management Architecture for WSNs (SCNA-WSN) to adopt an SOA and to provide web services for integrating heterogeneous cloud computing infrastructures. In SCNA-WSN, users access each resource as a service, eliminating the need to own the physical infrastructure, platform, or software. External applications can use web services to integrate SCNA-WSN. As a result, users can integrate and use various network management resources depending on system requirements. To protect service privacy and to preserve service scalability, an Advanced Encryption Standard (AES) security mechanism and a multicast overlay network are provided in the proposed SCNA-WSN. The proposed architecture is effective and secure. This architecture can provide sensor services with ubiquity, scalability and reliability. In this paper, we provide not only the theoretic analysis but also the implementation of an example system to demonstrate that an SCNA-WSN can decrease the difficulty of integrating different cloud platforms and heterogeneous sensor devices. Performance evaluations of the bandwidth cost and the service latency are presented.