物件導向軟體之架構(Object-Oriented Software Construction)探討

The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

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Internet of things: Vision, applications and research challenges

A mobile ad hoc network consists of wireless hosts that may move often. Movement of hosts results in a change in routes, requiring some mechanism for determining new routes. Several routing protocols have already been proposed for ad hoc networks. This report suggests an approach to utilize location information (for instance, obtained using the global positioning system) to improve performance of routing protocols for ad hoc networks.

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Location-aided routing (LAR) in mobile ad hoc networks

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

Parallel discrete event simulation (PDES), sometimes called distributed simulation, refers to the execution of a single discrete event simulation program on a parallel computer. PDES has attracted a considerable amount of interest in recent years. From a pragmatic standpoint, this interest arises from the fact that large simulations in engineering, computer science, economics, and military applications, to mention a few, consume enormous amounts of time on sequential machines. From an academic point of view, parallel simulation is interesting because it represents a problem domain that often contains substantial amounts of parallelism (e.g., see [59]), yet paradoxically, is surprisingly difficult to parallelize in practice. A sufficiently general solution to the PDES problem may lead to new insights in parallel computation as a whole. Historically, the irregular, data-dependent nature of PDES programs has identified it as an application where vectorization techniques using supercomputer hardware provide little benefit [14].A discrete event simulation model assumes the system being simulated only changes state at discrete points in simulated time. The simulation model jumps from one state to another upon the occurrence of an event. For example, a simulator of a store-and-forward communication network might include state variables to indicate the length of message queues, the status of communication links (busy or idle), etc. Typical events might include arrival of a message at some node in the network, forwarding a message to another network node, component failures, etc.We are especially concerned with the simulation of asynchronous systems where events are not synchronized by a global clock, but rather, occur at irregular time intervals. For these systems, few simulator events occur at any single point in simulated time; therefore parallelization techniques based on lock-step execution using a global simulation clock perform poorly or require assumptions in the timing model that may compromise the fidelity of the simulation. Concurrent execution of events at different points in simulated time is required, but as we shall soon see, this introduces interesting synchronization problems that are at the heart of the PDES problem.This article deals with the execution of a simulation program on a parallel computer by decomposing the simulation application into a set of concurrently executing processes. For completeness, we conclude this section by mentioning other approaches to exploiting parallelism in simulation problems.Comfort and Shepard et al. have proposed using dedicated functional units to implement specific sequential simulation functions, (e.g., event list manipulation and random number generation [20, 23, 47]). This method can provide only a limited amount of speedup, however. Zhang, Zeigler, and Concepcion use the hierarchical decomposition of the simulation model to allow an event consisting of several subevents to be processed concurrently [21, 98]. A third alternative is to execute independent, sequential simulation programs on different processors [11, 39]. This replicated trials approach is useful if the simulation is largely stochastic and one is performing long simulation runs to reduce variance, or if one is attempting to simulate a specific simulation problem across a large number of different parameter settings. However, one drawback with this approach is that each processor must contain sufficient memory to hold the entire simulation. Furthermore, this approach is less suitable in a design environment where results of one experiment are used to determine the experiment that should be performed next because one must wait for a sequential execution to be completed before results are obtained.

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Parallel discrete event simulation

This article describes iSMS, a platform that integrates IP networks with the short message service in mobile telephone systems. iSMS provides a generic gateway for creating and hosting wireless data services for mobile stations. Our approach does not require any modification to the mobile telephone system architecture. The iSMS system can be quickly developed and operated by a third party or end user without involvement of mobile equipment manufacturers and telecom operators. Based on the iSMS platform, we illustrate services such as e-mail delivery/forwarding, Web access (e.g., stock and train schedule query) and handset music services. The iSMS platform and the services have been implemented for GSM networks. With iSMS, users are able to use standard GSM handsets to access wireless Internet services, while other approaches like the Wireless Application Protocol and SIM Toolkit services require function-enabled MSs.

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iSMS: an integration platform for short message service and IP networks

Discrete event simulation is usually time consuming. Recently, there has been a great deal of interest in using parallel computers to speed up the simulation process. Before the parallel simulation approach is applied, it is important to understand the inherent parallelism of simulation applications. A simple technique called critical path analysis was proposed to study paralllelism of simulation applications. This paper describes three critical path analysis algorithms based on different event-scheduling (process scheduling) policies. These algorithms are much simpler than a previous approach, where the events must be recorded in a trace and an extra pass is required to process the event trace. In our approach, the critical path analysis algorithms are integrated with the sequential simulation. At the end of the sequential simulation, the optimal parallel execution time is also computed. Livny proposed an algorithm similar to our approach (His, however, was designed for a specific language). Our algorithms can be integrated with sequential simulation programs written by users or be integrated with simulation languages. Another advantage of our algorithms over previous approaches is that ours can be used to study load balancing under different event-scheduling policies. Since our algorithms can be easily inserted in sequential simulation programs, critical path analysis can be applied to existing sequential programs without difficulty. The results can then be used to predict the performance of parallel simulation on similar applications. An example is given to show how useful information can be obtained from our algorithms.

Parallelism analyzers for parallel discrete event simulation

This paper presents a new adaptive bandwidth allocation scheme to prevent handoff failure in wireless cellular networks, known as the measurement-based preassignment (MPr) technique. This technique is particularly useful in micro/pico cellular networks which offers quality-of-service (QoS) guarantee against call dropping. The proposed MPr scheme distinguishes itself from the well-known guarded channel (GC) based schemes in that it allows the handoff calls to utilize a prereserved channel pool before competing for the shared channels with new call arrivals. The key advantage of the proposed MPr scheme is that it enables easy derivation of the number of channels that needs to be reserved for handoff based on a predetermined handoff dropping probability, without the need for solving the often complex Markov chain required in GC schemes, thus, making the proposed MPr scheme simple and efficient for implementation. This is essential in handling multiple traffic types with potentially different QoS requirements. In addition, the MPr scheme is adaptive in that it can dynamically adjust the number of reserved channels for the handoff according to the periodical measurement of the traffic status within a local cell, thus completely eliminating the signaling overhead for status information exchange among cells mandated in most existing channel allocation schemes. Numerical results and comparisons are given to illustrate the tradeoff.

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An adaptive measured-based preassignment scheme with connection-level QoS support for mobile networks

Cellular telephony provides voice and data services to mobile users. To deliver these services, the cellular network can track the locations of the users, and can allow user movement during the conversations. It achieves these capabilities through small scale (handoff) and large scale (roaming) mobility management. The authors describe mobility management in cellular networks, including the details of different handoff schemes, location tracking schemes, and call delivery procedures.

https://ir.nctu.edu.tw:443/bitstream/11536/882/1/A1996VT90100010.pdf

Mobility management for cellular telephony networks

In general packet radio service (GPRS), a mobile station (MS) is tracked at the cell level during packet transmission, and is tracked at the routing-area (RA) level when no packet is delivered. A READY timer (RT) mechanism was proposed in 3GPP 23.060 to determine when to switch from cell tracking to RA tracking. In this mechanism, a threshold interval T is defined. If no packet is delivered within T, the MS is tracked at the RA level. When a packet arrives, the MS is tracked at the cell level again. However, the RT mechanism has a major fallacy in that the RTs in both the MS and the serving GPRS support node may lose synchronization. This paper considers another mechanism called READY counter (RC) to resolve this problem. In this approach, a threshold K is used. Like the RT approach, the MS is tracked at the cell level during packet transmission. If no packets are delivered after the MS has made K cell crossings, the MS is tracked at the RA level. We also devise an adaptive algorithm called dynamic RC (DRC). This algorithm dynamically adjusts the K value to reduce the location update and paging costs. We propose analytic and simulation models to investigate RC, RT, and DRC. Our study indicates that RC may outperform RT. We also show that DRC nicely captures the traffic-mobility patterns and always adjusts the K threshold close to the optimal values.

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Yi-Bing Lin

Papers

iSMS: an integration platform for short message service and IP networks

Parallelism analyzers for parallel discrete event simulation

An adaptive measured-based preassignment scheme with connection-level QoS support for mobile networks

Mobility management for cellular telephony networks

A mobility management strategy for GPRS