Journal of Interconnection Networks

Recently, multidimensional scaling (MDS) techniques have been successfully applied in the MDS-MAP method to the node localization problem of ad hoc networks, such as wireless sensor networks. MDS-MAP uses MDS to compute a local, relative map at each node from the distance or proximity information of its neighboring nodes. Based on the local maps and the locations of a set of anchor nodes with known locations, the absolute positions of unknown nodes in the network can be computed. In this paper, we investigate the effects of several variants of MDS on the accuracy of localization in wireless sensor networks. We compare metric scaling and non-metric scaling methods, each with several different optimization criteria. Simulation results show that different optimization models of metric scaling achieve comparable localization accuracy for dense networks and non-metric scaling achieves more accurate results than metric scaling for sparse networks at the expense of higher computational cost.

Nowadays, we can count several proposals about the micro-mobility problem in IP networks. In this paper, we try to summarize current proposals by means of a general classification scheme. Our taxonomy permits to identify pros and cons of current IP micromobility protocols. This classification should help understanding that e2e solutions do not cope with simultaneous movements of mobile nodes, and thus a mixed scheme would be better. Here, we design a new scheme, namely the smartAR scheme, which reduces network complexity and endures both single and simultaneous movements scenario. Moreover, we provide the classification of the IP micro-mobility protocols with a simple analysis of the hand-off latencies.

We present Delay-Energy Aware Routing (DEAP) a novel protocol for heterogeneous wireless ad hoc networks. DEAP is a crosslayer scheme that: first, manages adaptively the energy control by controlling the wakeup cycle of sensors based on the experienced packet delay; and second, rout packet in each hoc by distributing the load a group of neighboring nodes. The primary result of DEAP is that it enables a flexible and wide range of tradeoffs between the packet delay and the energy consumption. Therefore, DEAP supports delay sensitive applications of heterogeneous networks that include sensors and actors. DEAP is scalable to the change in network size, node type, node density and topology. DEAP accommodates seamlessly such network changes, including the presence of actors in heterogeneous sensor networks. Indeed, while DEAP does not count on actors, it takes advantage of them, and uses their resources when possible, thus reducing the energy consumption of sensor nodes. Through analysis and simulation evaluations, we show that DEAP improves the packet delay and network lifetime compared to other protocols.

Cross-layering represents a perspective design principle for adapting natively wired protocols to the wireless scenario and for improving their performance. The paper explores the possibilities of cross-layer design as a candidate tool for performance optimization, focusing on problems deriving from the usage of ARQ schemes in today's wireless networks and proposes a novel and general cross-layer interaction scheme between the transport and the link layers. Achieved results in the framework of a IEEE 802.11-based multi-hop wireless network demonstrate the value of the proposed framework, and allow to provide guidelines for future work on the topic.

Live traffic flow information can help improve the efficiency of a communication network. There are many ways available to monitor the traffic flow of a network. In this paper, we propose a very efficient monitoring strategy. This strategy not only reduces the number of nodes to be monitored but also determines the complete traffic information of the entire network using the information from the monitored nodes. The strategy is optimal for monitoring a network because it reduces the number of monitored nodes to a minimum. Fast algorithms are also presented in this paper to compute the traffic information for the entire network based on the information collected from the monitored nodes. The monitoring scheme discussed in this paper can be applied to the internet, telecommunication networks, wireless ad hoc networks, large scale multiprocessor computing systems, and other information systems where the transmission of information needs to be monitored.

To improve data accessibility in ad hoc networks, we have proposed a few methods of replicating data items on mobile hosts by considering the data access frequencies from mobile hosts to each data item and the network topology. In this paper, we address techniques to manage locations of data items or replicas and efficiently forward access requests to the locations. In order to manage locations of data items efficiently, a key issues is predicting the locations of data items that dynamically change. To predict the locations of data items, we use the information on replica allocation at every relocation time and the logs of past data accesses.

We investigate a known optimal lifetime solution for a linear wireless sensor network through simulation, and propose alternative solutions where a known optimal solution does not exist. The network is heterogeneous in the sensors' energy distribution and also in the amount of data each sensor must communicate. As a basis for comparison, we analyze the lifetime of a network using a simple, nearest-neighbor routing algorithm, and an analytic solution to the optimal lifetime of networks meeting certain constraints. Alternative solutions considered range from those requiring global knowledge of the network to solutions using only next-neighbor knowledge. We compare the performance of all the routing algorithms in simulation.

This paper introduces a novel scheduling problem called the active interval scheduling problem in hierarchical wireless sensor networks for long-term periodical monitoring applications. To improve the report sensitivity of the hierarchical wireless sensor networks, an efficient scheduling algorithm is desired. Therefore, in this paper, we propose a compact genetic algorithm (CGA) to optimize the solution quality for sensor network maintenance. The experimental result shows that the proposed CGA brings better solutions in acceptable calculation time.

Individual IEEE 802.15.4 clusters with separate coordinators can be interconnected to form larger sensor networks. In this paper, we investigate the performance of two 802.15.4 beacon enabled clusters interconnected in a master-slave manner. In this setup, the cluster coordinator of the source cluster periodically visits the sink cluster as an ordinary node, thus performing the bridging function. The bridge delivers its data to the sink coordinator using the dedicated slots allocated by the sink coordinator. We investigate the performance of the cluster, in particular the impact of the number of packet lanes allocated to the bridge.

Reputation mechanisms for detecting and punishing free-riders in ad hoc networks depend on the local detection of selfish behavior. Although naive selfish strategies based on dropping data packets are readily detected, more sophisticated strategies that manipulate ad hoc routing protocols present a greater challenge. In this work we develop a method to distinguish selfish peers from cooperative ones based solely on local observations of AODV routing protocol behavior. Our approach uses the finite state machine model of locally observed AODV actions to build up a statistical description of the behavior of each neighbor. We apply a series of well-known statistical tests to features derived from this description to partition the set neighboring nodes into a cooperative and selfish class. Simulation results for a non-mobile ad hoc network show that our approach can detect two different types of routing manipulation while maintaining a low rate of false positives.

This paper introduces a novel geometry-based simulation technique for the arbitrary indoor OFDM quality-of-service (QoS) analysis. This automatic geometry-driven approach integrates electromagnetic radio propagation modeling, channel characterization, and OFDM interference analysis to quantify the indoor OFDM performance through the off-site computer–aided procedures. Essential OFDM quality-of-service measures, such as signal-to-interference ratios (SIR) and bit error rates (BER) can be generated by this new analysis tool. The resulting QoS measure contours can be used by service providers and OFDM communication system designers to quantify the system performance and determine the optimal accessing locations for any indoor geometry.

Evolution in Wireless Technologies and Networks imposes a greater need for network support as current congestion control and avoidance techniques are mainly designed for wired networks. The current performance evaluation techniques proposed for wireless networks are not able to achieve optimal performance to guarantee desired Quality of Service (QoS) standards. Thus, the new schemes such as Active Queue Management (AQM) are needed to be adaptive to dynamic wireless networks and bursty traffic conditions to help in avoiding severe performance degradation in wireless environment. Thus, in this paper we developed and validated a novel approximate analytical performance model of a multiple threshold Random Early Detection (RED) congestion control mechanism based on the principle of Maximum Entropy (ME). It can be employed at the wireless gateways/base stations to regulate the buffer management and bandwidth allocation. Closed form expressions for the state and blocking probabilities have also been characterized. Numerical examples have been presented for aggregate and marginal QoS measures, which show the credibility of the ME solution and its validation against simulation.

Wireless networked sensors are envisioned to play a vital role in the emerging pervasive service platforms that will instrument a wide range of next generation civil and military applications. Recently, we have proposed ANSWER: AutoNomouS Wireless sEnsor netwoRk as a service platform whose mission is to provide dependable information services to in-situ mobile users while satisfying their quality-of-service (QoS) requirements. Alongside with the stationary tiny sensors, the network employs more powerful mobile devices referred to as aggregation and forwarding nodes (AFNs). ANSWER exploits AFN mobility to support QoS requirements. However, as an AFN moves closer to an event (for example, a hazardous spill), it may be at risk (for example, due to potential damage). In this paper, we present a quantitative analysis of the interplay and balance between QoS support and asset safety. We propose a new scheme, called SAFER (for SAFEty-aware Relocation), which pursues relocation of the AFN in order to boost network performance without unnecessarily compromising AFN safety. For the relocation process to take place, SAFER uses historical data on detected events and employs an evolutionary neural network to assess the risk involved and predict good quality new position(s). Experimental results demonstrate the effectiveness of SAFER.