A reinforcement learning-based routing for delay tolerant networks

Delay Tolerant Reinforcement-Based (DTRB) is a delay tolerant routing solution for IEEE 802.11 wireless networks which enables device to device data exchange without the support of any pre-existing network infrastructure. The solution utilizes Multi-Agent Reinforcement Learning techniques to learn about routes in the network and forward/replicate the messages that produce the best reward. The rewarding process is executed by a learning algorithm based on the distances between the nodes, which are calculated as a function of time from the last meetings. DTRB is a flooding-based delay tolerant routing solution. The simulation results show that DTRB can deliver more messages than a traditional delay tolerant routing solution does in densely populated areas, with similar end-to-end delay and lower network overhead.     

Coordinating a two-level supply chain with delay in payments and profit sharing

Achieving effective coordination among suppliers and retailers has become a pertinent research issue in supply chain management. Channel coordination is a joint decision policy achieved by a supplier(s) and a retailer(s) characterized by an agreement on the order quantity and the trade credit scenario (e.g., quantity discounts, delay in payments). This paper proposes a centralized model where players in a two-level (supplier–retailer) supply chain coordinate their orders to minimize their local costs and that of the chain. In the proposed supply chain model the permissible delay in payments is considered as a decision variable and it is adopted as a trade credit scenario to coordinate the order quantity between the two-levels. Computational results indicate that with coordination, the retailer orders in larger quantities than its economic order quantity, with savings to either both players, or to one in the supply chain. Moreover, a profit-sharing scenario for the distribution of generated net savings among the players in the supply chain is presented. Analytical and experimental results are presented and discussed to demonstrate the effectiveness of the proposed model.     

A dynamic programming method with lists for the knapsack sharing problem

In this paper, we propose a method to solve exactly the knapsack sharing problem (KSP) by using dynamic programming. The original problem (KSP) is decomposed into a set of knapsack problems. Our method is tested on correlated and uncorrelated instances from the literature. Computational results show that our method is able to find an optimal solution of large instances within reasonable computing time and low memory occupancy.     

Comparison of PI controllers designed for the delay model of TCP/AQM networks

One of the major problems of communication networks is congestion. In order to address this problem in TCP/IP networks, Active Queue Management (AQM) scheme is recommended. AQM aims to minimize the congestion by regulating the average queue size at the routers. To improve upon AQM, recently, several feedback control approaches were proposed. Among these approaches, PI controllers are gaining attention because of their simplicity and ease of implementation. In this paper, by utilizing the fluid-flow model of TCP networks, we study the PI controllers designed for TCP/AQM. We compare these controllers by first analyzing their robustness and fragility. Then, we implement these controllers in ns-2 platform and conduct simulation experiments to compare their performances in terms of queue length. Taken together, our results provide a guideline for choosing a PI controller for AQM given specific performance requirements.     

An optimal procedure for minimizing total weighted resource tardiness penalty costs in the resource-constrained project scheduling problem

We present an optimal solution procedure for minimizing total weighted resource tardiness penalty costs in the resource-constrained project scheduling problem. In this problem, we assume the constrained renewable resources are limited to very expensive equipments and machines that are used in other projects and are not available in all periods of time of a project. In other words, for each resource, there is a dictated ready date as well as a due date such that no resource can be available before its ready date but the resources are permitted to be used after their due dates by paying penalty cost depending on the resource type. We also assume that only one unit of each resource type is available and no activity needs more than it for execution. The objective is to determine a schedule with minimal total weighted resource tardiness penalty costs. For this purpose, we present a branch-and-bound algorithm in which the branching scheme starts from a graph representing a set of conjunctions (the classical finish-start precedence constraints) and disjunctions (introduced by the resource constraints). In the search tree, each node is branched to two child nodes based on the two opposite directions of each undirected arc of disjunctions. Selection sequence of undirected arcs in the search tree affects the performance of the algorithm. Hence, we developed different rules for this issue and compare the performance of the algorithm under these rules using a randomly generated benchmark problem set.     

VxWorks下共享中断的多串口卡驱动设计

本文介绍了嵌入式操作系统VxWorks下的串口驱动程序的结构和基于16C554芯片的多串口扩展卡，分析了共享中断的多串口扩展卡的标准驱动开发过程，最后介绍了简单的非标准驱动的实现方法。     

Joint fingerprinting and encryption in hybrid domains for multimedia sharing in social networks

The advent of social networks and cloud computing has made social multimedia sharing in social networks become easier and more efficient. The lowered cost of redistribution, however, also invites much motivation for large-scale copyright infringement, so it is necessary to safeguard multimedia sharing for security and privacy. In this paper, we proposed a novel framework for joint fingerprinting and encryption (JFE) based on Cellular Automata (CA) and social network analysis (SNA) with the purpose of protecting media distribution in social networks. The motivation is to map the hierarchical community structure of social networks into the tree structure of Discrete Wavelet Transform (DWT) for fingerprinting and encryption. First, the fingerprint code is produced by using SNA. Then the obtained fingerprints are embedded into the DWT domain. Afterwards, CA is used for permutation in the DWT domain. Finally, the image is diffused with XOR operation in the spatial domain. The proposed method, to the best of our knowledge, is the first JFE method using CA and SNA in hybrid domains for security and privacy in social networks. The use of fingerprinting along with encryption can provide a double-layer protection for media sharing in social networks. Both theoretical analysis and experimental results validate the effectiveness of the proposed scheme.     

A dynamic multicast tree based routing scheme without replication in delay tolerant networks

Delay tolerant networks (DTNs) are a special type of wireless mobile networks which may lack continuous network connectivity. Multicast is an important routing function that supports the distribution of data to a group of users: a service needed for many potential DTN applications. While multicasting in the Internet and in mobile ad hoc networks has been studied extensively, efficient multicasting in DTNs is a considerably different and challenging problem due to the probabilistic nature of contact among nodes. This paper aims to provide a non-replication multicasting scheme in DTNs while keeping the number of forwardings low. The address of each destination is not replicated, but is assigned to a particular node based on its contact rate level and active level. Our scheme is based on a dynamic multicast tree where each leaf node corresponds to a destination. Each tree branch is generated at a contact based on the compare–split rule proposed in this paper. The compare part determines when a new search branch is needed, and the split part decides how the destination set should be partitioned. When only one destination is left in the destination set, we use either wait (no further relay) or focus (with further relay) to reach the final destination. The effectiveness of our approach is verified through extensive simulations. Ratio-based-split performs best in the compare–split step, both in synthetic and real traces. Using the wait scheme can reduce the number of forwardings, while using the focus scheme can reduce the latency.     

A new method for computing delay margins for stability of linear delay systems

This note is concerned with stability properties of linear time-invariant delay systems. We consider delay systems of retarded type modeled both as a high order scalar differential-difference equation and as a set of first order differential-difference equations expressed in state space form. We provide a computational method that can be used to compute a delay interval such that the system under consideration is stable for all delay values that lie in the computed interval. This method requires computing only the eigenvalues and generalized eigenvalues of certain constant matrices and it can be implemented efficiently. Based on this method, we further state a simple necessary and sufficient condition concerning stability independent of delay for each of the two types of the models.     

A simple index rule for efficient traffic splitting over parallel wireless networks with partial information

Multi-path communication solutions provide a promising means to improve the network performance in areas covered by multiple wireless access networks. Today, little is known about how to effectively exploit this potential. We study a model where flows are transferred over multiple parallel networks, each of which is modeled as a processor sharing node. The goal is to minimize the expected transfer time of elastic data traffic by smartly dispatching the flows to the networks, based on partial information about the numbers of foreground and background flows in each of the nodes. In the case of full state information, the optimal policy can be derived via standard MDP-techniques, but for models with partial information an optimal solution is hard to obtain. An important requirement is that the splitting algorithm is efficient, yet simple, easy-to-implement, scalable in the number of parallel networks and robust against changes in the parameter settings. We propose a simple index rule for splitting traffic streams based on partial information, and benchmark the results against the optimal solution in the case of full state information. Extensive simulations with real networks show that this method performs extremely well under practical circumstances for a wide range of realistic parameter settings.     

A numerical algorithm for stability testing of fractional delay systems

This paper presents an effective numerical algorithm for testing the BIBO stability of fractional delay systems described by fractional-order delay-differential equations. It is based on using Cauchy's integral theorem and solving an initial-value problem. The algorithm has a reliable result which is illustrated by several examples, and hence is practically useful in the analysis and design of feedback control for both integer- and fractional-order systems having time delays.     

Hopfield networks for identification of delay differential equations with an application to dengue fever epidemics in Cuba

This work is aimed at proposing an algorithm, based upon Hopfield networks, for estimating the parameters of delay differential equations. This neural estimator has been successfully applied to models described by Ordinary Differential Equations, whereas its application to systems with delays is a novel contribution. As a case in point, we present a model of dengue fever for the Cuban case, which is defined by a delay differential system. This epidemiological model is built upon the scheme of an SIR (susceptible, infected, recovered) population system, where both delays and time-varying parameters have been included. The latter are thus estimated by the proposed neural algorithm. Additionally, we obtain an expression of the Basic Reproduction Number for our model. Experimental results show the ability of the estimator to deal with systems with delays, providing plausible parameter estimations, which lead to predictions that are coherent with actual epidemiological data. Besides, when the Basic Reproduction Number is computed from the estimated parameter values, results suggest an evolution of the epidemic that is consistent with the observed infection. Hence the estimation could help health authorities to both predict the future trend of the epidemic and assess the efficiency of control measures.     

Sensitivity analysis of the knapsack sharing problem: Perturbation of the weight of an item

In this paper, we study the sensitivity analysis of the optimum of the knapsack sharing problem (KSP) to the perturbation of the weight of an arbitrary item. We determine the interval limits of the weight of each perturbed item using a heuristic approach which reduces the original problem to a series of single knapsack problems. A perturbed item belongs either to an optimal class or to a non-optimal class. We evaluate the performance of the proposed heuristic on a set of problem instances of the literature. Encouraging results are obtained.     

Metaheuristics for the traveling salesman problem with pickups, deliveries and handling costs

This paper studies the Traveling Salesman Problem with Pickups, Deliveries, and Handling Costs. The subproblem of minimizing the handling cost for a fixed route is analyzed in detail. It is solved by means of an exact dynamic programming algorithm with quadratic complexity and by an approximate linear time algorithm. Three metaheuristics integrating these solution methods are developed. These are based on tabu search, iterated local search and iterated tabu search. The three heuristics are tested and compared on instances adapted from the related literature. The results show that the combination of tabu search and exact dynamic programming performs the best, but using the approximate linear time algorithm considerably decreases the CPU time at the cost of slightly worse solutions.     

On the energy-delay trade-off in geographic forwarding in always-on wireless sensor networks: A multi-objective optimization problem

The design and development of multi-hop wireless sensor networks are guided by the specific requirements of their corresponding sensing applications. These requirements can be associated with certain well-defined qualitative and/or quantitative performance metrics, which are application-dependent. The main function of this type of network is to monitor a field of interest using the sensing capability of the sensors, collect the corresponding sensed data, and forward it to a data gathering point, also known as sink. Thus, the longevity of wireless sensor networks requires that the load of data forwarding be balanced among all the sensor nodes so they deplete their battery power (or energy) slowly and uniformly. However, some sensing applications are time-critical in nature. Hence, they should satisfy strict delay constraints so the sink can receive the sensed data originated from the sensors within a specified time bound. Thus, to account for all of these various sensing applications, appropriate data forwarding protocols should be designed to achieve some or all of the following three major goals, namely minimum energy consumption, uniform battery power depletion, and minimum delay. To this end, it is necessary to jointly consider these three goals by formulating a multi-objective optimization problem and solving it. In this paper, we propose a data forwarding protocol that trades off these three goals via slicing the communication range of the sensors into concentric circular bands. In particular, we discuss an approach, called weighted scale-uniform-unit sum, which is used by the source sensors to solve this multi-objective optimization problem. Our proposed data forwarding protocol, called Trade-off Energy with Delay (TED), makes use of our solution to this multi-objective optimization problem in order to find a “best” trade-off of minimum energy consumption, uniform battery power depletion, and minimum delay. Then, we present and discuss several numerical results to show the effectiveness of TED. Moreover, we show how to relax several widely used assumptions in order to enhance the practicality of our TED protocol, and extend it to real-world network scenarios. Finally, we evaluate the performance of TED through extensive simulations. We find that TED is near optimal with respect to the energy × delay metric. This simulation study is an essential step to gain more insight into TED before implementing it using a sensor test-bed.     

A polynomial time approximation scheme for embedding hypergraph in a weighted cycle

The problem of Minimum Congestion Hypergraph Embedding in a Weighted Cycle (MCHEWC) is to embed the hyperedges of a hypergraph as paths in a weighted cycle such that the maximum congestion is minimized. This problem is NP-hard. In this paper, we present a polynomial time approximation scheme (PTAS) for this problem.     

A fuzzy trust evaluation method for knowledge sharing in virtual enterprises

The success of virtual enterprises (VEs) depends on the effective sharing of related resources between various enterprises or workers who perform related activities. Specifically, VE success hinges on the integration and sharing of information and knowledge. Trust is an important facilitator of knowledge sharing. However, the trustworthiness of a peer is a vague concept that is dynamic and that often shifts over time or with environmental changes. This study designs a trust-based knowledge-sharing model based on characteristics of VEs and the knowledge structure model to express knowledge associated with VE activities. Subsequently, the factors that affect the trust evaluation are identified based on the characteristics of trust and VEs. Finally, this study develops a knowledge sharing, decision-making framework in which a fuzzy trust evaluation method for sharing knowledge is proposed based on VE activities and the interactions among workers in allied enterprises. The method consists of three sub-methods, including an activity correlation evaluation method, a current trust evaluation method, and an integral trust evaluation method. Under the premises of secure VE knowledge and reasonable access authorization, the proposed knowledge-sharing method provides the trust level between a knowledge-requesting enterprise and a knowledge-supplying enterprise to improve the willingness of the latter to share more valuable knowledge, ultimately increasing the efficiency and competitiveness of VEs.