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

Network Virtual Machine (NetVM): A New Architecture for Efficient and Portable Packet Processing Applications

A challenge facing network device designers, besides increasing the speed of network gear, is improving its programmability in order to simplify the implementation of new applications (see for example, active networks, content networking, etc). This paper presents our work on designing and implementing a virtual network processor, called NetVM, which has an instruction set optimized for packet processing applications, i.e., for handling network traffic. Similarly to a Java Virtual Machine that virtualizes a CPU, a NetVM virtualizes a network processor. The NetVM is expected to provide a compatibility layer for networking tasks (e.g., packet filtering, packet counting, string matching) performed by various packet processing applications (firewalls, network monitors, intrusion detectors) so that they can be executed on any network device, ranging from expensive routers to small appliances (e.g. smart phones). Moreover, the NetVM will provide efficient mapping of the elementary functionalities used to realize the above mentioned networking tasks upon specific hardware functional units (e.g., ASICs, FPGAs, and network processing elements) included in special purpose hardware systems possibly deployed to implement network devices

The Design of a System Architecture for Mobile Multimedia Computers

This chapter discusses the system architecture of a portable computer, called Mobile Digital Companion, which provides support for handling multimedia applications energy efficiently. Because battery life is limited and battery weight is an important factor for the size and the weight of the Mobile Digital Companion, energy management plays a crucial role in the architecture. As the Companion must remain usable in a variety of environments, it has to be flexible and adaptable to various operating conditions. The Mobile Digital Companion has an unconventional architecture that saves energy by using system decomposition at different levels of the architecture and exploits locality of reference with dedicated, optimised modules. The approach is based on dedicated functionality and the extensive use of energy reduction techniques at all levels of system design. The system has an architecture with a general-purpose processor accompanied by a set of heterogeneous autonomous programmable modules, each providing an energy efficient implementation of dedicated tasks. A reconfigurable internal communication network switch exploits locality of reference and eliminates wasteful data copies

Task allocation in group of nodes in the IoT: A consensus approach

The realization of the Internet of Things (IoT) paradigm relies on the implementation of systems of cooperative intelligent objects with key interoperability capabilities. In order for objects to dynamically cooperate to IoT applications' execution, they need to make their resources available in a flexible way. However, available resources such as electrical energy, memory, processing, and object capability to perform a given task, are often limited. Therefore, resource allocation that ensures the fulfilment of network requirements is a critical challenge. In this paper, we propose a distributed optimization protocol based on consensus algorithm, to solve the problem of resource allocation and management in IoT heterogeneous networks. The proposed protocol is robust against links or nodes failures, so it's adaptive in dynamic scenarios where the network topology changes in runtime. We consider an IoT scenario where nodes involved in the same IoT task need to adjust their task frequency and buffer occupancy. We demonstrate that, using the proposed protocol, the network converges to a solution where resources are homogeneously allocated among nodes. Performance evaluation of experiments in simulation mode and in real scenarios show that the algorithm converges with a percentage error of about±5% with respect to the optimal allocation obtainable with a centralized approach