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

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial