# Performance and Challenges of Service-Oriented Architecture for Wireless Sensor Networks
## 6 Service-Oriented Middleware (SOM) Architectures Approaches for WSNs
### Other SOM Architectures for WSNs
By using two different regions of two different nodes, the network adjusts itself to the node with the highest power. The limitation of this approach is that there is no strategy for low-cost QoS monitoring processes, detection of QoS degradation, and data or service aggregation exists. The QoS degradation can be addressed by using the monitoring frequency approach [60]. This approach is more cost-effective than static or dynamic approaches. The management of the system and service should focus on the node and service level. The data aggregation in a sensor network can deal with simple data; however, it cannot deal with complex data. Furthermore, many approaches of SOM architectures attempt to implement a flexible and scalable architecture with less cost. In this study, authors present an elastic sensor actor network (ESANET) environment [61], which proved to be more cost-effective. These applications run on top of SANET shared resources. ESANET is a software system that can bridge the gap between existing software and the next generation of SANET. The Role Oriented Adaptive Architecture (ROAA) is used to build a collaborative and adaptive ESANET software. The middleware architecture is used to achieve the goal of ESANET. The security mechanism is applied to the Nano kernel Middleware, an outside and inside security mechanism within the system. The limitation of this approach is that it does not provide details about the system's performance, accuracy, and overhead. The issues of integrating SOM architecture with sensor networks in the internet of things (IoT) technology were addressed in [62]. The authors proposed this type of SOA based on the middleware architecture. The features of SOA include a publish/subscribe mechanism that mediates communication between the IoT technology and the applications of existing automation systems. The publish/subscribe mechanism monitors traffic and manages asynchronous events. The IoT appears as either wireless sensors or identification tags. The middleware allows a smooth integration between heterogeneous technologies within applications [62]. According to [63], the existing Laboratory Information Management System (LIMS) at the Center for Life Science Automation (CELISCA) laboratories combined SOA with WSNs (SOA-WSNs) [63]. This approach relied on Sensor Web Enablement (SWE) and Sensor Observation Services (SOS) that provided the sensor measurement of data in different WSNs [63]. The architecture used a DPWS-based web service to assist in the cooperation, abstraction, and device orchestration of the LIMS services. In Life Science Automation (LSA), Carbon Monoxide (CO) and Hydrogen (H2) must be regulated by sensors [63]. Unfortunately, WSNs do not support these dangerous gases. However, SOA-WSNs in LIMS were designed to detect any of these risks and block any disasters within LSA to guarantee a valid analysis procedure. The LSA observation service analyzes the actual sensor readings and will release the necessary responses in the case of any abnormalities. The flexibility, usability, and extensibility of this architecture is increased through a developed WSN-based service infrastructure. In [63], the researchers claim that this approach decreases cost and setup times. However, since no results were provided, this approach cannot be fairly evaluated.