Real-life performance of protocol combinations for wireless sensor networks

Wireless sensor networks today are used for many and diverse applications like nature monitoring, or process and wireless building automation. However, due to the limited access to large testbeds and the lack of benchmarking standards, the real-life evaluation of network protocols and their combinations remains mostly unaddressed in current literature. To shed further light upon this matter, this paper presents a thorough experimental performance analysis of six protocol combinations for TinyOS. During these protocol assessments, our research showed that the real-life performance often differs substantially from the expectations. Moreover, we found that combining protocols is far from trivial, as individual network protocols may perform very different in combination with other protocols. The results of our research emphasize the necessity of a flexible generic benchmarking framework, powerful enough to evaluate and compare network protocols and their combinations in different use cases

Supporting protocol-independent adaptive QoS in wireless sensor networks

Next-generation wireless sensor networks will be used for many diverse applications in time-varying network/environment conditions and on heterogeneous sensor nodes. Although Quality of Service (QoS) has been ignored for a long time in the research on wireless sensor networks, it becomes inevitably important when we want to deliver an adequate service with minimal efforts under challenging network conditions. Until now, there exist no general-purpose QoS architectures for wireless sensor networks and the main QoS efforts were done in terms of individual protocol optimizations. In this paper we present a novel layerless QoS architecture that supports protocol-independent QoS and that can adapt itself to time-varying application, network and node conditions. We have implemented this QoS architecture in TinyOS on TmoteSky sensor nodes and we have shown that the system is able to support protocol-independent QoS in a real life office environment

When should I use network emulation ?

The design and development of a complex system requires an adequate methodology and efficient instrumental support in order to early detect and correct anomalies in the functional and non-functional properties of the tested protocols. Among the various tools used to provide experimental support for such developments, network emulation relies on real-time production of impairments on real traffic according to a communication model, either realistically or not. This paper aims at simply presenting to newcomers in network emulation (students, engineers, ...) basic principles and practices illustrated with a few commonly used tools. The motivation behind is to fill a gap in terms of introductory and pragmatic papers in this domain. The study particularly considers centralized approaches, allowing cheap and easy implementation in the context of research labs or industrial developments. In addition, an architectural model for emulation systems is proposed, defining three complementary levels, namely hardware, impairment and model levels. With the help of this architectural framework, various existing tools are situated and described. Various approaches for modeling the emulation actions are studied, such as impairment-based scenarios and virtual architectures, real-time discrete simulation and trace-based systems. Those modeling approaches are described and compared in terms of services and we study their ability to respond to various designer needs to assess when emulation is needed

When Should I Use Network Emulation?

The design and development of a complex system requires an adequate methodology and efficient instrumental support in order to early detect and correct anomalies in the functional and non-functional properties of the tested protocols. Among the various tools used to provide experimental support for such developments, network emulation relies on real-time production of impairments on real traffic according to a communication model, either realistically or not. This paper aims at simply presenting to newcomers in network emulation (students, engineers, ...) basic principles and practices illustrated with a few commonly used tools. The motivation behind is to fill a gap in terms of introductory and pragmatic papers in this domain. The study particularly considers centralized approaches, allowing cheap and easy implementation in the context of research labs or industrial developments. In addition, an architectural model for emulation systems is proposed, defining three complementary levels, namely hardware, impairment and model levels. With the help of this architectural framework, various existing tools are situated and described. Various approaches for modeling the emulation actions are studied, such as impairment-based scenarios and virtual architectures, real-time discrete simulation and trace-based systems. Those modeling approaches are described and compared in terms of services and we study their ability to respond to various designer needs to assess when emulation is needed

Service-Oriented Multigranular Optical Network Architecture for Clouds

This paper presents a novel service-oriented network architecture to bridge the informational gap between user applications and optical networks providing technology-agnostic multigranular optical network services for clouds. A mediation layer (service plane) between user applications and network control is proposed to facilitate a mapping process between user application requests and the network services. At the network level, a multigranular optical network (MGON) is proposed and implemented to support dynamic wavelength and subwavelength granularities with different transport formats [optical burst switched (OBS), optical burst transport (OBT)], reservation protocols (one-way, two-way), and different quality-of-service (QoS) levels per service type. The service-oriented multigranular optical network has been designed, implemented, and demonstrated on an experimental testbed. The testbed consists of service and network resource provisioning, service abstraction, and network resource virtualization. The service-to-network interoperation is provided by means of a gateway that maps service requests to technology-specific parameters and a common signaling channel for both service and network resource provisioning