In this paper, we propose SAFE (Security Aware FlexRay scheduling Engine), to provide a problem definition and a design framework for FlexRay static segment schedule to address the new challenge on security. From a high level specification of the application, the architecture and communication middleware are synthesized to satisfy security requirements, in addition to extensibility, costs, and end-to-end latencies. The proposed design process is applied to two industrial case studies consisting of a set of active safety functions and an X-by-wire system respectively.

Error estimating coding has attracted significant attention recently. It enables a receiver to estimate bit error rate (BER) of a partially correct packet. Our study in this paper shows that based on the popular M-QAM modulation schemes, symbol errors have a well-defined structure, which is ultimately translated into a strong correlation in the BER of bits that constitute a symbol. We leverage this correlation to design smart error estimating coding (Smart-EEC). Smart-EEC can be used to boost the estimating accuracy of error estimating codes, e.g., EEC. Through extensive evaluation, we demonstrate that Smart-EEC helps EEC achieve a much better tradeoff between the space redundancy and estimating accuracy.

With the improving performance of microprocessors, their bandwidth and latency requirements have increased at a rate much faster than the network's ability to provide them. The performance bottleneck has gradually shifted from the processors to the interconnection network. Traditional electrical interconnection, because of its low bandwidth, high delay and low interconnection density, becomes one of the constraints of high-performance computer(HPC)'s further improvement. Due to the inherent limitations of the electrical interconnection network, optical interconnection has become a feasible way to improve the performance. A Three-Dimensional Optical Interconnection Network (TDOIN) with low latency and high throughput was put forward in our previous work. An accurate mathematical model can help us design and optimize the optical networks. However, there is not a mathematical model which can provide an accurate analysis for TDOIN. To make better use of the network, we propose a steady-state model to evaluate TDOIN's network characteristics in this paper. This mathematical model is constructed by using Probability Theory. The results of the model analysis and the simulation shows that our model can accurately depict behaviors of TDOIN at steady state.

Multicore platforms are increasingly used in real-time embedded applications. In control systems, including automotive, avionics, and automation, resources shared by tasks on different cores need to be protected by mechanisms that guarantee access in a mutually exclusive way with bounded worst case blocking time. The evaluation of the tradeoffs among the possible protocols for mutual exclusion requires an estimate of their implementation overheads. In this paper, we summarize the possible protection mechanisms and provide code implementations in real-time operating systems executing on a multicore platform. We discuss the tradeoffs among the different mechanisms based on experimental evaluation of their memory and timing overheads as well as their impact on system schedulability. We propose a heuristic algorithm to select the optimal combination of mechanisms for shared resources in systems with time constraints to minimize their memory requirements. The effectiveness of the optimization procedure is demonstrated by synthetic systems as well as industrial case studies.

ABSTRACT Network coding provides a powerful mechanism for improving performance of wireless networks. In this paper, we present an analytical approach for end‐to‐end delay analysis in wireless networks that employs inter‐session network coding. Prior work on performance analysis in wireless network coding mainly focuses on the throughput of the overall network. Our approach aims to analyze the delay of each flow in the network. The theoretical basis of our approach is network calculus. In order to use network calculus to analyze the performance of traffic flows in the network, we have to address three specific problems: identifying traffic flows, characterizing broadcast links, and measuring coding opportunities. We propose solutions for these problems and discuss the practical issues when applying the approach in practice. We make three main contributions. First, we obtain theoretical formulations for computing the queueing delay bounds of traffic flows in wireless networks with network coding. Second, with the formulations, we figure out the factors that affect the queueing delay of a flow and find that first‐in first‐out scheduling cannot fully exploit the benefit of network coding. Third, in order to exploit our findings, we introduce a new scheduling scheme that can improve the performance of current practical wireless network coding. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT In this paper, we propose a relatively complete and robust optimization model under the scenario where multisecondary users cooperatively sense multi‐channels. The objective of this model is to maximize the system throughput, meanwhile aims to jointly optimize the parameters including the sensing time and the weight coefficients of the sampling results. Because this model is a nonlinear optimization model, we instead adopt a heuristic sequential parameters optimization method (SPO) to solve the model. The method begins with deriving the lower bound of the objective function of the optimization model. Then, it maximizes this lower bound by optimizing the weight coefficients through solving a series of suboptimal problems using Lagrange method. Given that the weight coefficients are found, it finally transforms the problem into another monotonic programming problem and exploits a fast‐convergent polyblock algorithm to find an optimized sensing time parameter. We finally conduct extensive experiments by simulations. The results demonstrate that, in terms of the throughput gained by the system, SPO can deliver a solution that is up to 99.3% of the optimal on average, which indicates that SPO can solve the proposed optimization model effectively. In addition, we also show the performance advantage of the proposed model on improving the system throughput by comparing with other state‐of‐the‐art optimization models. Wireless Communications and Mobile Computing. Copyright © 2012 John Wiley & Sons, Ltd.

The error patterns of a wireless channel can be represented by a binary sequence of ones (burst) and zeros (run), which is referred to as a trace. Recent surveys have shown that the run length distribution of a wireless channel is an intrinsically heavy-tailed distribution. Analytical models to characterize such features have to deal with the trade-off between complexity and accuracy. In this paper, we use an independent but not identically distributed (inid) stochastic process to characterize such channel behavior and show how to parameterize the inid bit error model on the basis of a trace. The proposed model has merely two parameters both having intuitive meanings and can be easily figured out from a trace. Compared with chaotic maps, the inid bit error model is simple for practical use but can still be deprived from heavy-tailed distribution in theory. Simulation results demonstrate that the inid model can match the trace, but with fewer parameters. We then propose an improvement on the inid model to capture the ‘bursty’ nature of channel errors, described by burst length distribution. Our theoretical analysis is supported by an experimental evaluation.

In this paper, we investigate the construction of error estimating codes and propose a content-based error estimation coding framework(CBEEC). The CBEEC captures the bur sty nature of channel errors and provides a better estimation than that of EEC proposed by Chen et.al. Specifically, the core technique of the CBEEC is that each bit of a group is chosen consecutively from the original data bits and the number of '1's in each group is taken as error estimating bits. We provide the estimation quality, redundancy, and computational overhead in theory, respectively. We conduct experiments, in which an ad hoc wireless network is set up and partial packets are collected for error estimation. Experimental results show that 90% estimated errors are below 60 bits for a partial packet with 12000 bits, which outperforms EEC significantly.

Network coding provides a powerful mechanism for improving performance of wireless networks. In this paper, we present an analytical approach for end-to-end delay analysis in wireless networks that employ inter-session coding. Prior work on performance analysis in wireless network coding mainly focuses on the throughput of the overall network. Our approach aims to analyze the end-to-end delay performance of each flow in the network. The theoretical basis of our approach is network calculus. In order to apply network calculus to the analysis of wireless network coding, we address three specific problems: identifying traffic flows, characterizing broadcast links, and measuring coding opportunities. We make three main contributions. First, we obtain theoretical formulations for computing the delay bounds of bursty flows in wireless networks employing network coding. Second, based on the formulations, we figure out the factors that affect the end-to-end delays, and find an interesting phenomenon that, as traffic grows, the overall delay can potentially decrease. Third, in order to exploit the benefit of our findings, we introduce a new scheduling scheme that can improve the performance of current practical wireless network coding.

Existing literature in Cooperative Cognitive Radio Networks (CCRNs) always assumed a scenario where only one Primary User (PU) and several Secondary Users (SUs) coexist. However, in practice, multi-PUs and multi-SUs always coexist and the number of SUs is usually greater than that of PUs. Under such complex yet real scenarios, we assume that each PU not only allows a set of SUs to access its pre-allocated channel, but can leverage some of these SUs to improve its transmission rate via cooperative technologies. We consider a joint channel allocation and cooperation set partition problem in CCRNs, in which we aim to allocate a channel and assign a cooperation set that consists of several SUs for each PU, such that for a given period of time, the average transmission rates gained by all the users achieve maximum proportional fairness. We formulate the problem as a 0-1 non-linear programming model. Due to its NP-hardness, we propose a suboptimal Centralized Genetic Algorithm (CGA) for the problem. Extensive simulations demonstrate that CGA not only converges rapidly, but is shown to perform as well as 92% of the optimal solution delivered by brutal search, in terms of the fitness that reflects the fairness degree of the transmission performance gained by all the users.

Existing studies on the design of routing protocols for wireless ad hoc networks mainly focused on energy efficiency. However, in many real-time applications such as target tracking and bush fire surveillance, latency is an important concern, and little attention has been paid to it in the design of routing protocols for such applications to meet the specified Quality of Service (QoS) requirements like the end-to-end latency constraint. In this paper we propose an energy-aware, opportunistic routing protocol EARTOR for requests with QoS constraints, through striking the elegant balance between the energy consumption and the end-to-end latency. Our objective is to maximize the number of requests realized when dealing with a sequence of requests arrived one by one. The core techniques adopted include the cross-layer design that incorporates the duty cycle, a bidding mechanism for each relay candidate that takes its residual energy, location information, and relay priority into consideration. We finally conduct experiments by simulations to evaluate the performance of the proposed protocol against existing ones, in terms of the dynamic delivery ratio and the network capacity. The experimental results demonstrated that the proposed protocol outperforms the state-of-the-art protocols significantly.

Barrier coverage is known to be an appropriate model of coverage for movement detection and boundary guard, which is achieved by barriers of sensors. This paper is focused on how to achieve strong k-barrier coverage with mobile sensors energy-efficiently. We first design an approximation algorithm CBGB to achieve strong 1-barrier coverage energy-efficiently, and the performance of CBGB is close to the optimal solution. Then, we propose a Divide-and-Conquer algorithm to achieve strong k-barrier coverage for large sensor networks. Simulations demonstrate the effectiveness of the proposed algorithm for achieving k-barrier coverage.

Wireless ad hoc networks consist of hundreds to thousands of mobile nodes that are powered by batteries. To prolong the network operational time, energy conservation in such networks is of paramount importance. Energy optimization thus is one major objective in the design of routing protocols. However, in some stringent real-time applications including target tracking and bushfire surveillance, latency is an important concern, and little attention has been paid to it in the design of routing protocols for such applications to meet the specified Quality of Service (QoS) requirements like the end-to-end latency constraint. In this paper we focus on online energy-aware routing protocol design for routing requests to meet various end-to-end latency constraints under the multi-rate environment, we aim to maximize the network lifetime through striking the right balance among the node's transmission rate, the end-to-end latency, and energy consumption. Specifically, due to the NP-hardness of the problem of concern, we propose a joint optimization framework consisting of finding a routing path and assigning a specific transmission rate at each node in the path for each request such that the total energy consumption is minimized. We also devise novel heuristic algorithms for the problem, based on different energy cost metrics. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms in terms of network lifetime. The experimental results show that the proposed algorithm incorporating the energy utilization ratio of the residual energy of a node to its initial energy capacity into the cost metric outperforms the others significantly.

In network-on-chip (NoC), computing worst-case delay bounds for packet delivery is crucial for designing predictable systems but yet an intractable problem. This paper presents an analysis technique to derive per-flow communication delay bound. Based on a network contention model, this technique, which is topology independent, employs network calculus to first compute the equivalent service curve for an individual flow and then calculate its packet delay bound. To exemplify this method, this paper also presents the derivation of a closed-form formula to compute a flow's delay bound under all-to-one gather communication. Experimental results demonstrate that the theoretical bounds are correct and tight.

Most of the present optical interconnect networks within the high performance computers require either the buffering and opto-electonic conversion of the data packets or the pre-assigning of the optical path from the source to destination, which to a certain extent influence the performance metrics such as latency and throughput. Aiming at the limitation mentioned above, a hybrid optical-electrical interconnection for high performance computer system named bufferless optical interconnection network (BOIN) is brought forward together with the link control protocol and deadlock/livelock free routing algorithms. The upper bound of the data transmission latency within BOIN is also given. Experimental simulation is based on the comparison of BOIN and the other two similar networks. The results show that BOIN has advantages over the other two that it can deliver high throughput at low latency, which can well satisfy the need for high performance computing systems.

In network-on-chip, computing worst-case delay bound for packet delivery is crucial for designing predictable systems but yet an intractable problem due to complicated resource contention scenarios. In this paper, we present an analysis technique to derive the communication delay bound for individual flows. Based on a network contention model, this technique, which is topology independent, employs the network calculus theory to first compute the equivalent service curve for individual flows and then calculate their packet delay bound. To exemplify our method, we also present the derivation of a closed-form formula to calculate the delay bound for all-to-one gather communication. Our experimental results demonstrate the theoretical bounds are correct and tight.

Advanced integration technologies enable the construction of Network-on-Chip (NoC) from two dimensions to three dimensions. Studies have shown that 3D NoCs can improve average communication performance because of the possibility of using the additional dimension to shorten communication distance. In this paper, we present a detailed case study on worst-case communication performance in regular k-ary-2-mesh networks. Through both analysis and simulation, we show that, while 3D networks achieve better average performance, this may not be the case for worst-case performance mainly due to constraints on vertical channels. Our analysis is based on network calculus, which allows to calculate theoretical delay bounds for constrained flows traversing network elements. Categories and Subject Descriptors B.4 [Input/Output and Data Communications]: Performance Analysis and Design Aids General Terms Design, Performance

This paper proposes a framework for the application of residuation theory in network calculus. Min-plus convolution and deconvolution composes a dual-residuated pair, their properties can be studied by using residuation theory. End-to-end performance bounds can also be obtained by residuation method. The application of residuation theory in max-plus network calculus theory and time varying network calculus are also studied.

To achieve scalability, a few resource-rich heterogeneous nodes are scattered in a wireless sensor network consisting of a large number of energy-constrained sensor nodes. Heterogeneous nodes are equipped with powerful radio transceiver and their main task is to organize a backbone communication network and to relay data to the sink. For the scenario, this paper proposes a coverage problem which maintaining relay connectivity at the same time in heterogeneous wireless sensor networks. The goal is to find a minimum relay connected set cover (MRCSC) which satisfies (1) active nodes in set cover fully sense the whole task area. Motivated by triangular lattice with asymptotic optimality, we address a rule for restricting irregularity spread to form an approximate nice triangular lattice, (2) active nodes are relay connected which means any active node connects to at least one heterogeneous node with a given success data forwarding rate. Simulations show that the coverage of MRCSC nearly reaches that of OGCD, but relay connectivity of active nodes is strongly reinforced with limited count of additional nodes.

In packet-switched network-on-chip, computing worst-case delay bounds is crucial for designing predictable and cost-effective communication systems but yet an intractable problem due to complicated resource sharing scenarios. For wormhole networks with credit-based flow control, the existence of cyclic dependency between flit delivery and credit generation further complicates the problem. Based on network calculus, we propose a technique for analyzing communication delay bounds for individual flows in wormhole networks. We first propose router service analysis models for flow control, link and buffer sharing. Based on these analysis models, we obtain a buffering-sharing analysis network, which is open-ended and captures both flow control and link sharing. Furthermore, we compute equivalent service curves for individual flows using the network contention tree model in the buffer-sharing analysis network, and then derive their delay bounds. Our experimental results verify that the theoretical bounds are correct and tight.

Wireless sensor and actor networks (WSANs) are composed of a large number of sensors and a small number of (mobile) resource-rich actors. Sensors gather information about the physical phenomenon, while actors take decisions and then perform appropriate actions upon the environment.In this paper, a single-actor selection algorithm for WSANs is addressed from hops and energy constraints. The corresponding optimal solution HBMECT (Hop-Bounded and Minimum Energy Cost Tree) is determined by integer linear programming (ILP). And then, a distributed approximate algorithm of HBMECT is provided.In the performance evaluation, the approximate algorithm of HBMECT is compared with MECT (Minimum Energy Cost Tree) and MPCT (Minimum Path Cost Tree) algorithms.

In this paper, we propose a novel limited path algorithm called LPUA to deal with two constrained unicast QoS routing problems, which is known as NP complete. By combining two weights linearly into a single one, Dijkstra algorithm based on the single weight can be used directly to return a least cost path between the source node and the destination node. When a routing request comes, LPUA only needs to compute a limited number of paths. If any of these paths cannot meet the routing constraints, the routing request would be refused. Extensive simulations have show that LPUA is very efficient.

Active Queue Management (AQM) is a very active research area in networking. The main objective of an AQM mechanism is to provide low delay and low loss service in best-effort service networks. In this paper we propose a new AQM algorithm based on the feedback compensation technique in control theory. The algorithm is called Proportional Integral based series compensation, and Position feedback compensation (PIP). By choosing the appropriate feedback compensation element and its parameters, the properties of the corrected system become dependent, to a great extent, on the series and feedback compensatory elements. Thus, PIP can eliminate the error incurred by the inaccuracy in the linear system model as well as eliminate the sensitivity to the changes in system parameters like load level, propagation delay, etc. The performance of PIP is compared to PI using ns simulations. From the experiments and analysis we conclude that PIP is more responsive to and robust under time-varying network conditions than PI.