Optimized usage of network resources based on context information

Today an efficient (cost-effective) design and usage of networks is of particular importance. As more and more computer systems become context-aware the question of how context information can be used to improve computer networks arises. In this poster we describe how context information can be used to optimize the usage of resources in a computer network. By means of a mobile payment system we show how these optimization method can be applied

A Comprehensive Experimental Comparison of Event Driven and Multi-Threaded Sensor Node Operating Systems

The capabilities of a sensor network are strongly influenced by the operating system used on the sensor nodes. In general, two different sensor network operating system types are currently considered: event driven and multi-threaded. It is commonly assumed that event driven operating systems are more suited to sensor networks as they use less memory and processing resources. However, if factors other than resource usage are considered important, a multi-threaded system might be preferred. This paper compares the resource needs of multi-threaded and event driven sensor network operating systems. The resources considered are memory usage and power consumption. Additionally, the event handling capabilities of event driven and multi-threaded operating systems are analyzed and compared. The results presented in this paper show that for a number of application areas a thread-based sensor network operating system is feasible and preferable

Improving the Energy Efficiency of the MANTIS Kernel

Event-driven operating systems such as TinyOS are the preferred choice for wireless sensor networks. Alternative designs following a classical multi-threaded approach are also available. A popular implementation of such a multi-threaded sensor network operating system is MANTIS. The event-based TinyOS is more energy efficient than the multi-threaded MANTIS system. However, MANTIS is more capable than TinyOS of supporting time critical tasks as task preemption is supported. Thus, timeliness can be traded for energy efficiency by choosing the appropriate operating system. In this paper we present a MANTIS kernel modification that enables MANTIS to be as power efficient as TinyOS. Results from an experimental analysis demonstrate that the modified MANTIS can be used to fit both sensor network design goals of energy efficiency and timeliness

BurstProbe: Debugging Time-Critical Data Delivery in Wireless Sensor Networks

In this paper we present BurstProbe, a new technique to accurately measure link burstiness in a wireless sensor network employed for time-critical data delivery. Measurement relies on shared probing slots that are embedded in the transmission schedule and used by nodes to assess link burstiness over time. The acquired link burstiness information can be stored in the node's flash memory and relied upon to diagnose transmission problems when missed deadlines occur. Thus, accurate diagnosis is achieved in a distributed manner and without the overhead of transmitting rich measurement data to a central collection point. For the purpose of evaluation we have implemented BurstProbe in the GinMAC WSN protocol and we are able to demonstrate it is an accurate tool to debug time-critical data delivery. In addition, we analyze the cost of implementingBurstProbe and investigate its effectiveness

Detailed Diagnosis of Performance Anomalies in Sensornets

We address the problem of analysing performance anomalies in sensor networks. In this paper, we propose an approach that uses the local flash storage of the motes for logging system data, in combination with online statistical analysis. Our results show not only that this is a feasible method but that the overhead is significantly lower than that of communication-centric methods, and that interesting patterns can be revealed when calculating the correlation of large data sets of separate event types.GINSENGCONE

Adaptive split transmission for video streams in wireless mesh networks

Wireless mesh networks hold great promise in the wireless transmission of video flows, particularly if the problem of providing sufficient network capacity can be addressed. For this reason, schemes which help to address this difficulty in capacity-limited wireless networks are of great interest. This paper presents a novel and simple algorithm, adaptive split transmission algorithm, for achieving real-time, and quality-guaranteed video transmission in wireless mesh networks. The algorithm utilizes the unused capacities of multiple channels rather than trying to transmit the flow over just one overloaded channel. The flow is efficiently split into several sub-flows in a capacity-aware manner, each sub-flow then being transmitted through different channels in parallel. The adaptive split transmission algorithm controls flows dynamically in response to changes in the states of the available channels, thereby avoiding the overloading of any one channel. We evaluate the algorithm through simulations. The results show that the adaptive split transmission algorithm achieves synchronized, quality-guaranteed, and real-time wireless video transmission. The proposed algorithm can be used for interactive real-time wireless video applications without changing current wireless hardware, MAC protocols and upper-layer protocols

ARBITER: Adaptive rate-based intelligent HTTP streaming algorithm

Dynamic Adaptive streaming over HTTP (DASH) is widely used by content providers for video delivery and dominates traffic on cellular networks. The inherent variability in both video bitrate and network bandwidth negatively impacts the user Quality of Experience (QoE), motivating the design of better DASH-compliant adaptation algorithms. In this paper we present ARBITER, a novel streaming adaptation algorithm that explicitly integrates the variations in both video and network dynamics in its adaptation decisions. Our simulation-based performance evaluation, using real video content and cellular bandwidth traces, shows that ARBITER achieves an excellent tradeoff among streaming metrics in terms of received video quality, stall count, stall duration, and switching dynamics, leading to a relative improvement of 17-45% in user QoE in comparison to state-of-the-art algorithms

MiniNAM: A network animator for visualizing real-time packet flows in Mininet

In this demonstration we present MiniNAM, a utility that provides real-time animation of networks created by the Mininet emulator. Mininet is one of the most well-known network emulators in research and academia. Although Mininet is capable of emulating both traditional and software-defined networks, it does not provide a tool to visually observe and monitor the packets flowing over the created network topology. Our utility includes all the components required to initiate, visualize and modify Mininet network flows in real-time. MiniNAM provides a graphical user interface that allows dynamic modification of preferences and packet filters: a user can view selective flows with options to color code packets based on packet type and/or source node. This establishes MiniNAM as a very powerful tool for debugging network protocols or teaching, learning and understanding network concepts. This demonstration illustrates a number of sample use cases and examples of using MiniNAM to create networks and view the generated network flows with customized preferences

A Cooja-based tool for coverage and fifetime evaluation in an in-building sensor network.

Contiki’s Cooja is a very popular wireless sensor network (WSN) simulator, but it lacks support for modelling sensing coverage, focusing instead on network connectivity and protocol performance. However, in practice, it is the ability of a sensor network to provide a satisfactory level of coverage that defines its ultimate utility for end-users. We introduce WSN-Maintain, a Cooja-based tool for coverage and network lifetime evaluation in an in-building WSN. To extend the network lifetime, but still maintain the required quality of coverage, the tool finds coverage redundant nodes, puts them to sleep and automatically turns them on when active nodes fail and coverage quality decreases. WSN-Maintain together with Cooja allow us to evaluate different approaches to maintain coverage. As use cases to the tool, we implement two redundant node algorithms: greedy-maintain, a centralised algorithm, and local-maintain, a localised algorithm to configure the initial network and to turn on redundant nodes. Using data from five real deployments, we show that our tool with simple redundant node algorithms and reading correlation can improve energy efficiency by putting more nodes to sleep