Ubiquitous RFID: Where are we?

After over a half century of development, radio-frequency identification (RFID) is beginning to move into mainstream applications for automatic identification. RFID is widely seen today as one of the key enabling technologies of the “Internet of Things”. However, many challenges still need to be addressed before we can fully benefit from this nascent and ubiquitous technology. In this paper, we present the state of the art of RFID technology and discuss the challenges and open issues in developing next generation RFID applications.     

An Insightful Marginal Cost Analysis for an Electric Utility Capacity Planning Problem

Given a situation in which a finite number of load curves occur with either known probabilities or over nonoverlapping fractions of time, the problem addressed herein is to conduct a marginal cost analysis for allocating to the various load curves, the capital costs of equipments used in an optimal capacity expansion plan. Such an allocation may be used, for example, in determining a marginal cost time-of-day pricing scheme. A recent paper solves this problem through a formal mathematical programming duality approach. The purpose of the present paper is to first demonstrate that closed form expressions for such marginal cost capital allocations can be readily obtained through an intuitive and insightful perturbation analysis, without any recourse to mathematical programming techniques. Hence, a practitioner can therefore more easily understand and interpret the available duality results. Furthermore, the analysis contained in this paper helps to unify and generalize some existing contributions in the literature, and sheds light on the extent of information contained in the so-called equivalent load duration curve. By way of this analysis, a new set of easier to use and more general capital cost allocation formulae are also obtained.     

On the capacity of multiuser MIMO networks with interference

Maximizing the total mutual information of multiuser multiple-input multiple-output (MIMO) systems with interference is a challenging problem. In this paper, we consider the power control problem of finding the maximum sum of mutual information for a multiuser network with mutually interfered MIMO links. We propose a new and powerful global optimization method using a branch-and-bound (BB) framework, coupled with a novel reformulation-linearization technique (RLT). The proposed BB/RLT guarantees finding a global optimum for multiuser MIMO networks with interference. To reduce the complexity of BB/RLT, we propose a modified BB variable selection strategy to accelerate the convergence process. Numerical examples are also given to demonstrate the efficacy of the proposed solution.     

Improving End System Performance for Multimedia Applications over High Bandwidth Networks

Digital video services, scientific visualization and other multimedia applications require delivery of high network throughput to end user applications. In this paper we identify bottlenecks in the data path between high-speed networks and applications. Using performance of multimedia applications as a metric, the effectiveness of solutions to reduce network, operating system, and user bottlenecks is explored experimentally.     

Equivalent primal and dual differentiable reformulations of the Euclidean multifacility location problem

In this paper, we consider two equivalent differentiable reformulations of the nondifferentiable Euclidean multifacility location problem (EMFLP). The first of these is derived via a Lagrangian dual approach based on the optimum of a linear function over a unit ball (circle). The resulting formulation turns out to be identical to the known dual problem proposed by Francis and Cabot [1]. Hence, besides providing an easy direct derivation of the dual problem, this approach lends insights into its connections with classical Lagrangian duality and related results. In particular, it characterizes a straightforward recovery of primal location decisions. The second equivalent differentiable formulation is constructed directly in the primal space. Although the individual constraints of the resulting problem are generally nonconvex, we show that their intersection represents a convex feasible region. We then establish the relationship between the Karush-Kuhn-Tucker (KKT) conditions for this problem and the necessary and sufficient optimality conditions for EMFLP. This lends insights into the possible performance of standard differentiable nonlinear programming algorithms when applied to solve this reformulated problem. Some computational results on test problems from the literature, and other randomly generated problems, are also provided.     

Evaluating IPv6 on Windows and Solaris

IPv6 might solve several of IPv4's shortcomings, but the longer headers and address space add overhead that affects a range of performance metrics for both TCP and UDP. We established a test bed to compare the two protocol stacks along a set of six performance metrics. We also compared two IPv6 implementations running on Windows 2000 and Solaris 8 using identical hardware and settings. We performed additional tests using different configurations, including a pair of commercial routers that support dual IPv4-IPv6 stacks. While the majority of those results are beyond this article's scope, some of our experiences with the routers raised points that we address here.     

A precedence-constrained asymmetric traveling salesman model for disassembly optimization

In this paper, we address a product-disassembly optimization problem, which aims at minimizing the costs associated with the disassembly process (namely, the cost of breaking the joints and the sequence-dependent set-up cost associated with the disassembly operations), while maximizing the benefits resulting from the recovery of components and subassemblies that constitute the product. A method able to capture the mating relationships among the parts and joints of the product through a network representation scheme is developed. The disassembly optimization problem is formulated as a precedence-constrained asymmetric traveling salesman problem. A three-stage iterative procedure is designed to obtain optimal or near-optimal solutions to the problem. The results demonstrate that our procedure generates solutions that are within 2% of optimality for all test cases, while only requiring a reasonable computational effort.     

TMS-RFID: Temporal management of large-scale RFID applications

In coming years, there will be billions of RFID tags living in the world tagging almost everything for tracking and identification purposes. This phenomenon will impose a new challenge not only to the network capacity but also to the scalability of event processing of RFID applications. Since most RFID applications are time sensitive, we propose a notion of Time To Live (TTL), representing the period of time that an RFID event can legally live in an RFID data management system, to manage various temporal event patterns. TTL is critical in the “Internet of Things” for handling a tremendous amount of partial event-tracking results. Also, TTL can be used to provide prompt responses to time-critical events so that the RFID data streams can be handled timely. We divide TTL into four categories according to the general event-handling patterns. Moreover, to extract event sequence from an unordered event stream correctly and handle TTL constrained event sequence effectively, we design a new data structure, namely Double Level Sequence Instance List (DLSIList), to record intermediate stages of event sequences. On the basis of this, an RFID data management system, namely Temporal Management System over RFID data streams (TMS-RFID), has been developed. This system can be constructed as a stand-alone middleware component to manage temporal event patterns. We demonstrate the effectiveness of TMS-RFID on extracting complex temporal event patterns through a detailed performance study using a range of high-speed data streams and various queries. The results show that TMS-RFID has a very high throughput, namely 170,000–870,000 events per second for different highly complex continuous queries. Moreover, the experiments also show that the main structure to record the intermediate stages in TMS-RFID does not increase exponentially with the number of events. These results demonstrate that TMS-RFID not only supports high processing speeds, but is also highly scalable.     

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.