Context-aware RAON middleware for opportunistic network

Application development and deployment on Mobile Ad Hoc Networks (MANET) is a major challenge in the widespread use of MANET. The increasing D2D communication in 5G networks has renewed interest in an effective middleware design for MANET where application developers face various challenges such as unstable connectivity, high error rate, mobility induced disruption and disconnection, and limited battery power. We find that unstructured overlay network provides a good abstraction to facilitate application development and deployment on MANET. In this paper, we present the design of a middleware that builds a Resource-Aware Overlay Network (RAON), which is an unstructured overlay network of nodes engaged in the application that employs a query–reply mechanism for resource discovery. RAON is enhanced with features such as proactive neighbor replacement, congestion-aware data download and cooperative caching. Simulation results show that these features are effective in reducing query delay, improving data availability, and balancing node power consumption with protocol performance. We also present the middleware software design that offers the API based on node and path abstractions to applications. The middleware implements a generic context framework for acquiring device and user context. We discuss the implementation of application-level multicast and credit-based file-sharing applications using the middleware API. The middleware is implemented in Java J2ME on Android, which is tested in an ad hoc network of Nexus 7 devices running OLSR.     

A survey on routing techniques in underwater wireless sensor networks

Underwater Wireless Sensor Networks (UWSNs) are finding different applications for offshore exploration and ocean monitoring. In most of these applications, the network consists of significant number of sensor nodes deployed at different depths throughout the area of interest. The sensor nodes located at the sea bed cannot communicate directly with the nodes near the surface level; they require multi-hop communication assisted by appropriate routing scheme. However, this appropriateness depends not only on network resources and application requirements but also on environmental constraints. All these factors provide a platform where a resource-aware routing strategy plays a vital role to fulfill the different application requirements with dynamic environmental conditions. Realizing the fact, significant attention has been given to construct a reliable scheme, and many routing protocols have been proposed in order to provide an efficient route discovery between the sources and the sink. In this paper, we present a review and comparison of different algorithms, proposed recently in order to fulfill this requirement. The main purpose of this study is to address the issues like data forwarding, deployment and localization in UWSNs under different conditions. Later on, all of these are classified into different groups according to their characteristics and functionalities.     

Self-adaptive corner detection on MPSoC through resource-aware programming

Multiprocessor system-on-chip (MPSoC) designs offer a lot of computational power assembled in a compact design. In mobile robotic applications, they offer the chance to replace several dedicated computing boards by a single processor, which typically leads to a significant acceleration of the computer-vision algorithms employed. This enables robots to perform more complex tasks at lower power budgets, less cooling overhead and, ultimately, smaller physical dimensions.However, the presence of shared resources and dynamically varying load situations leads to low throughput and quality for corner detection; an algorithm very widely used in computer-vision. The contemporary operating systems from the domain have not been designed for the management of highly parallel but shared computing resources.In this paper, we evaluate resource-aware programming as a means to overcome these issues. Our work is based on Invasive Computing, a MPSoC hardware and operating-system design for resource-aware programming. We evaluate this system with real-world algorithms, like Harris and Shi–Tomasi corner detectors. Our results indicate that resource-aware programming can lead to significant improvements in the behavior of these detectors, with up to 22 percent improvement in throughput and up to 20 percent improvement in accuracy.     

Activity-based simulation using DEVS: increasing performance by an activity model in parallel DEVS simulation

Improving simulation performance using activity tracking has attracted attention in the modeling field in recent years. The reference to activity has been successfully used to predict and promote the simulation performance. Tracking activity, how- ever, uses only the inherent performance information contained in the models. To extend activity prediction in modeling, we propose the activity enhanced modeling with an activity meta-model at the meta-level. The meta-model provides a set of interfaces to model activity in a specific domain. The activity model transformation in subsequence is devised to deal with the simulation difference due to the heterogeneous activity model. Finally, the resource-aware simulation framework is implemented to integrate the activity models in activity-based simulation. The case study shows the improvement brought on by activity-based simulation using discrete event system specification （DEVS）.