Sujoy Ray

QoS-aware middleware for web services composition: a qualitative approach

Web services exhibit major industrial benefit by their ability to participate in composition processes. Web services composition allows for automated exchange of information among remote processes through the service interface. A well-established end-to-end QoS infrastructure among the involved processes precludes confusion among the developers, vendors and consumers. Most of the research work conducted in this domain has focused on functional QoS requirements such as service response time, delay, cost, etc. This paper elaborates the QoS of web services from the perspective of data freshness and accuracy. Towards this aim, the ‘Region Switching’ (RS) algorithm is introduced in this paper. Within the context of the multiple web services composition scenario, the RS-algorithm allows for accurate identification of the point of information change and the appropriate re-computation over the subset of the pre-established, global service execution plan. Thereafter, a mathematical model is presented to verify the need for re-computation based on certain estimated factors, computed thresholds, and the model design. Such a selective re-computation is worth considering since some services may take a significant amount of time to produce results where a slight change to the information set might not alter the outcome of the service. The proposed concept is implemented by utilising and extending the WS-Notification specification in order to elaborate a middleware that is capable of sensing and routing information change at the level of web services using the publish-subscribe mechanism. The contribution of this paper is threefold. First, it highlights the importance of qualifiable QoS aspect related to the issue of web services composition and monitoring. Second, it describes an algorithm capable of capturing and reflecting the state of web services involved in a composition process, thereby achieving higher QoS. Finally, the paper illustrates the use and extension of the WS-Notification concept in building such systems that would deliver up-to-date information to the user through selective re-computation of the web services composition plan.

The multi-depot split-delivery vehicle routing problem: Model and solution algorithm

Abstract Logistics and supply-chain management may generate notable operational cost savings with increased reliance on shared serving of customer demands by multiple agents. However, traditional logistics planning exhibits an intrinsic limitation in modeling and implementing shared commodity delivery from multiple depots using multiple agents. In this paper, we investigate a centralized model and a heuristic algorithm for solving the multi-depot logistics delivery problem including depot selection and shared commodity delivery. The contribution of the paper is threefold. First, we elaborate a new integer linear programming (ILP) model, namely: Multi-Depot Split-Delivery Vehicle Routing Problem (MDSDVRP) which allows establishing depot locations and routes for serving customer demands within the same objective function. Second, we illustrate a fast heuristic algorithm leveraging knowledge gathering in order to find near-optimal solutions. Finally, we provide performance results of the proposed approach by analyzing known problem instances from different VRP problem classes. The experimental results show that the proposed algorithm exhibits very good performance when solving small and medium size problem instances and reasonable performance for larger instances.

What middleware for network centric operations

The main intent of this paper is to address the issue of middleware in network centric operations. To this end, we characterize a set of Information Technology capabilities that such a middleware should implement. Afterwards, we will discuss the design and architectural aspects of these capabilities. This will lead us to an efficient and practical decision support system that we call a digital cockpit. The latter is essentially a multi-tier IT platform that provides a plethora of services such as: data and service integration, monitoring, analysis, and process optimization. Moreover, the platform uses advanced display mechanisms to render the information in a structured and navigational representation that offers the possibility to drill down into the details. A significant subgoal of the paper is to discuss the quality attributes of such an NCO middleware. Finally, we present the results of an implementation of the aforesaid platform architecture.

Energy-Efficient Monitor Deployment in Collaborative Distributed Setting

Monitoring large supply networks can be efficiently performed by employing active radio-frequency identification (a-RFID) sensors. Relay nodes collect and process workflow information from the sensors. The knowledge derived from the collected information is periodically communicated to monitors using onboard energy sources. Energy can be saved by communicating with closer monitors. In this setup, multiple decision makers with their own deployment budget collaborate to deploy monitors for minimizing energy consumption of the relay nodes. The contribution of this paper is threefold. It elaborates a mathematical model for distributed monitor deployment in budget-constrained supply-chain networks, it proposes a heuristic technique to find near-optimal allocation of monitors in tractable manner, and it illustrates a collaborative procedure to jointly minimize energy consumption along with a fair sharing of total deployment cost among multiple decision makers. The approach is presented through a case study. In addition, benchmark results are provided for a number of problem instances.

A decentralized heuristic for multi-depot split-delivery vehicle routing problem

We introduce a Multi-Point Stochastic Insertion Cost Gradient Descent (MuPSICGD) heuristic algorithm to solve multi-depot split-delivery vehicle routing problem (MDSD-VRP) through an innovative approach. We also describe two solution improvement techniques that can further enhance a fairly good solution. Our contribution is threefold: First we present a heuristic-based mechanism to solve multi-depot, multi-vehicle per depot routing problems in split-delivery setting. Second, unlike related meta-heuristics approaches, we construct solutions from connecting fragments. This can be very helpful in projecting a fitting solution estimate during the searching mechanism along with the potential for adaptability to exogenous events during routing execution. Third, the approach is suitable for decentralized implementation as long as the operating nodes cooperate on solving a common problem instance. In this respect, we elaborate the decentralization procedure. The proposed technique is also resilient to the loss or addition of computing nodes. We also provide a case study, implementation guidelines and suitable benchmarks based on known problem instances.

Mechanism design for decentralized vehicle routing problem

In this paper, we present a strategyproof mechanism design to tackle the multi-depot vehicle routing problem in multi-agent setting. In a small-world network environment (any node is connected to every other node through a short path) wherein different self-interested agencies are controlling their own vehicle fleets, we use an innovative game theoretic approach to distribute products to customers without any central authority. The game is using a reverse Vickrey auction that takes place in several rounds until all customers are assigned. Payments are given to depots as incentive for fairness of serving cost offering. The procedure leads to overall near-optimal routing for serving all customers. We briefly describe the use of a heuristic approach to solve the game-based procedure in bounded time and memory. We also provide benchmarks for several known problem instances.

Verification of data pattern for interactive privacy preservation model

The research problem of privacy-preserving data publishing is to release microdata in an aggregated form using distinguished techniques that will effectively conceal sensitive and private information but can be used by external users to exercise data mining. These techniques are often studied in interactive and non-interactive settings. While non-interactive setting mainly deals with the data publication using anonymization or noise addition approaches, interactive models are based on noisy response of queries. Most of the data pattern verification and classification accuracy determination approaches exist for non-interactively published microdata. In this paper, we verify the data pattern and determine classification accuracy on an interactive privacy preservation model called differential privacy. The contributions of this paper are: (1) We present a concise literature review of non-interactive and interactive models and technologies. (2) We propose an approach of retrieving information along with investigating, understanding and comparing the data classification accuracy experimentally on Privacy Integrated Queries. (3) We verify data pattern by comparing the correlation and classification accuracy of the differentially private data with non-interactive k-anonymous data.

Gossiping Based Distributed Plan Monitoring

Abstract Joint plan execution is gaining momentum due to its benefits in terms of cost effectiveness and operational agility. In this paper, we introduce a lightweight gossip based multi-agent distributed protocol for plan execution monitoring in a dynamic environment characterized by unreliable communication links and exogenous events. The information obtained from the monitoring process can be used as support for detecting plan deviations and applying corrective measures. The contribution of this paper consists in the elaboration of an agent centric information sharing mechanism that is resilient to adverse changes in the execution environment by exhibiting a high degree of tolerance to communication errors. The distributed monitoring procedure is elaborated along with a relevant case study and experimental results.

Model checking based service delivery planning

Service delivery planning may often involve plan specific ordering or sequencing especially in non-euclidean transit environments. Common approaches for vehicle routing fall short in adequately handling compound ad-hoc plan dependent constraints. We address multi-agent service provisioning by starting from different initial nodes of shared irregular transport graphs. We employ concurrent and interleaved dynamics composition to capture agent based service delivery problems as transition systems and related goal state properties that can be the subject of symbolic model checking. Formally verifying the negation of the goal state property allows to generate a counter example such that, if it exists, the route allocation planning problem finds a solution. The state explosion is mitigated by bounded model checking that has the additional advantage of providing counter examples of minimal length which correspond to minimized agent tours under a cost bound.

Evolutionary learning algorithm for reliable facility location under disruption

Abstract Facility location represents an important supply chain problem aiming at minimizing facility establishment and transportation cost to meet customer demands. Many facility location problem (FLP) instances can be modelled as p-median problems (PMP) and uncapacitated facility location (UFL) problems. While, most solution approaches assume totally reliable deployed facilities, facilities often experience disruptions and their failure often leads to a notably higher cost. Therefore, determination of facility locations and fortification of a subset of them within a limited budget are crucial to supply chain organizations to provide cost effective services in presence of probable disruptions. We propose an evolutionary learning technique to near-optimally solve two research problems: Reliable p-Median Problem and Reliable Uncapacitated Facility Location Problem considering heterogeneous facility failure probabilities, one layer of backup and limited facility fortification budget. The technique is illustrated using a case study and its performance is evaluated via benchmark results. We also provide an analysis on the effects on facility location by prioritizing customer demands and adopting geographic distance calculation. The approach allows fast generation of cost-effective and complete solution using reasonable computing power. Moreover, the underlying technique is customizable offering a trade-off between solution quality and computation time.