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

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

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

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

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

A Visual Programming Framework for Wireless Sensor Networks in Smart Home Applications

International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2015). 7 to 9, Apr, 2015. Singapure, Singapore.In this paper, we build upon the Internet of Things (IoT) paradigm, with aim of delivering networked solutions that enable to connect not only single sensors, but also whole wireless sensor networks (WSN) to the Internet in a secure, simple and efficient way, and describe the design and implementation of a smart-home management system. The system is composed of a lightweight tool with an intuitive user interface for commissioning of IPenabled WSN with constrained capabilities. The solution includes a visual programming interface with a common framework for discovering smart home services on the constrained WSN, and a code analysis and translation engine to generate python code. This engine analyses the application rules defined with the graphical user interface and translates them into distributed application scripts. The system also includes modules to plan the optimization of the deployment, and deploy and start the generated code. A prototype of the system, with the visual programming solution and code generation module developed is presented in this paper

Worst-case delay control in multigroup overlay networks

This paper proposes a novel and simple adaptive control algorithm for the effective delay control and resource utilization of end host multicast (EMcast) when the traffic load becomes heavy in a multigroup network with real-time flows constrained by (sigma, rho) regulators. The control algorithm is implemented at the overlay networks and provides more regulations through a novel (sigma, rho, lambda) regulator at each group end host who suffers from heavy input traffic. To our knowledge, it is the first work to incorporate traffic regulators into the end host multicast to control heavy traffic output. Our further contributions include a theoretical analysis and a set of results. We prove the existence and calculate the value of the rate threshold rho* such that for a given set of K groups, when the average rate of traffic entering the group end hosts rho macr > rho*, the ratio of the worst-case multicast delay bound of the proposed (sigma, rho, lambda) regulator over the traditional (sigma, rho) regulator is O(1/Kn) for any integer n. We also prove the efficiency of the novel algorithm and regulator in decreasing worst-case delays by conducting computer simulations

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