Wann sind Lieferaufträge profitabel?

The paper aims to optimize the final part of a firm’s value chain with regard to attended last-mile deliveries. It is assumed that to be profitable, e-commerce businesses need to maximize the overall value of fulfilled orders (rather than their number), while also limiting costs of delivery. To do so, it is essential to decide which delivery requests to accept and which time windows to offer to which consumers. This is especially relevant for attended deliveries, as delivery fees usually cannot fully compensate costs of delivery given tight delivery time windows. The literature review shows that existing order acceptance techniques often ignore either the order value or the expected costs of delivery. The paper presents an iterative solution approach: after calculating an approximate transport capacity based on forecasted are accepted or rejected expected delivery requests and a cost-minimizing routing, actual delivery requests aiming to maximize the overall value of orders given the computed transport capacity. With the final set of accepted requests, the routing solution is updated to minimize costs of delivery. The presented solution approach combines well-known methods from revenue management and time-dependent vehicle routing. In a computational study for a German metropolitan area, the potential and the limits of value-based demand fulfillment as well as its sensitivity regarding forecast accuracy and demand composition are investigated.     

A case for Passive Application Layer Multicast

Over the last few years, application-layer multicast (ALM) has emerged as a plausible solution for supporting group-oriented applications. However, ALM suffers from inefficiency due to its reliance on end hosts and potentially significant changes at both the server and client applications. In this paper, we propose an approach, PALM (Passive Application Layer Multicast), that removes the need for changes to the server or client applications while allowing for dynamic discovery of supporting network devices and client-side OS modules. The passive nature of the approach comes from the fact that bandwidth savings occur transparently with zero required modifications to the networking environment, similar to approaches such as web caching. We demonstrate the performance improvements of PALM relative to ALM and compare the benefits versus network-level multicast and separate unicast approaches through both simulation and experimental studies.     

Extending Proxy Caching Capability: Issues and Performance

Proxy caching is an effective approach to reduce the response latency to client requests, web server load, and network traffic. Recently there has been a major shift in the usage of the Web. Emerging web applications require increasing amount of server-side processing. Current proxy protocols do not support caching and execution of web processing units. In this paper, we present a weblet environment, in which, processing units on web servers are implemented as weblets. These weblets can migrate from web servers to proxy servers to perform required computation and provide faster responses. Weblet engine is developed to provide the execution environment on proxy servers as well as web servers to facilitate uniform weblet execution. We have conducted thorough experimental studies to investigate the performance of the weblet approach. We modify the industrial standard e-commerce benchmark TPC-W to fit the weblet model and use its workload model for performance comparisons. The experimental results show that the weblet environment significantly improves system performance in terms of client response latency, web server throughput, and workload. Our prototype weblet system also demonstrates the feasibility of integrating weblet environment with current web/proxy infrastructure.     

Providing scalable Web services using multicast communication

The recent growth in use of the World-Wide Web in the Internet has caused a significant increase in the demand placed on Web servers. This increased load results in noticeably longer response times for users. We propose an approach to using multicast in the delivery of Web resources that reduces the load on servers as well as the networks that connect them. We analyze the issues involved in using multicast in the Web, especially those related to routing and addressing, and present an alternative approach to multicast routing that is appropriate for this application. We also describe the design and implementation of a system based on the existing WWW client and server architecture and the multicast support provided within IP. Experimental results from this implementation are presented.     

Minimizing bandwidth requirements for on-demand data delivery

Two recent techniques for multicast or broadcast delivery of streaming media can provide immediate service to each client request, yet achieve considerable client stream sharing which leads to significant server and network bandwidth savings. The paper considers: 1) how well these recently proposed techniques perform relative to each other and 2) whether there are new practical delivery techniques that can achieve better bandwidth savings than the previous techniques over a wide range of client request rates. The principal results are as follows: First, the recent partitioned dynamic skyscraper technique is adapted to provide immediate service to each client request more simply and directly than the original dynamic skyscraper method. Second, at moderate to high client request rates, the dynamic skyscraper method has required server bandwidth that is significantly lower than the recent optimized stream tapping/patching/controlled multicast technique. Third, the minimum required server bandwidth for any delivery technique that provides immediate real-time delivery to clients increases logarithmically (with constant factor equal to one) as a function of the client request arrival rate. Furthermore, it is (theoretically) possible to achieve very close to the minimum required server bandwidth if client receive bandwidth is equal to two times the data streaming rate and client storage capacity is sufficient for buffering data from shared streams. Finally, we propose a new practical delivery technique, called hierarchical multicast stream merging (HMSM), which has a required server bandwidth that is lower than the partitioned dynamic skyscraper and is reasonably close to the minimum achievable required server bandwidth over a wide range of client request rates     

Optimized distributed delivery of continuous-media documents over unreliable communication links

Video-on-demand (VoD) applications place very high requirements on the delivery medium. High-quality services should provide for a timely delivery of the data-stream to the clients plus a minimum of playback disturbances. The major contributions of this paper are that it proposes a multiserver, multi-installment (MSMI) solution approach (sending the document in several installments from each server) to the delivery problem and achieves a minimization of the client waiting time, also referred to as the access time (AT) or start-up latency in the literature. By using multiple spatially distributed servers, we are able to exploit slow connections that would otherwise prevent the deployment of video-on-demand-like services, to offer such services in an optimal manner. Additionally, the delivery and playback schedule that is computed by our approach is loss-aware in the sense that it is flexible enough to accommodate packet losses without interrupts. The mathematical framework presented covers both computation and optimization problems associated with the delivery schedule, offering a complete set of guidelines for designing MSMI VoD services. The optimizations presented include the ordering of the servers and determining the number of installments based on the packet-loss probabilities of the communication links. Our analysis guarantees the validity of a delivery schedule recommended by the system by providing a percentage of confidence for an uninterrupted playback at the client site. This, in a way, quantifies the degree of quality of service rendered by the system and the MSMI strategy proposed. The paper is concluded by a rigorous simulation study that showcases the substantial advantages of the proposed approach and explores how optimization of the schedule parameters affects performance.     

Intelligent content-based document delivery via automatic filtering profile generation

We develop an intelligent document delivery approach for filtering text information. Our approach can conduct content-based filtering via a machine learning technique which automatically constructs a filtering profile from training examples. The profiles, encoded in rule representation, are easily understood by human. Good features of high predictive power for the learning process are automatically extracted from the document content. As a result, our approach is able to operate without any prior information or restriction of the topic areas and yet achieve the filtering task. We have conducted an extensive simulation study to analyze the performance of our approach. We have also implemented a practical intelligent news article delivery system based on our approach. Both simulation study as well as practical experiments use real-world document collections and the results demonstrate that our approach is effective. ©1999 John Wiley & Sons, Inc.     

Effective client-driven three-level rate adaptation (TLRA) approach for adaptive HTTP streaming

Multimedia streaming allows consumers to view multimedia content anywhere. However, quality of service is a major concern amid heightened levels of network traffic caused by increasing user demand. Accordingly, media streaming technology is adopting a new paradigm: adaptive HTTP streaming (AHS). AHS is widely used for real-time streaming content delivery in the Internet environment. In streaming, selection of appropriate bitrate is crucial for adapting media rate to network variations and client processing capabilities while ensuring optimal service for the consumer. We evaluate a proposed client-driven three-level optimized rate adaptation algorithm for adaptive HTTP media streaming. In the first stage, the algorithm chooses a suitable starting bitrate close to the available channel capacity. Next, the algorithm monitors the client parameters in real time, precisely detecting network variations and choosing a likely available bit representation for the next download segment. The algorithm controls and minimizes the effects of buffer stalls and overflow resulting from the brief network variations occurring between consecutive segments. The proposed algorithm is implemented in Dynamic Adaptive Streaming over HTTP (DASH) player and its performance compared to that of commercially available Gstreamer-based HTTP Live Streaming (HLS) and DASH players which use conventional segment fetch time–based adaptation and throughput-based adaptation algorithms respectively. This evaluation uses a real-time cloud server client and test bed streaming setup. The resulting analysis shows that the client-driven three-level rate adaptation (TLRA) approach allows adaptive streaming clients to maximize use of end-to-end network capacity, delivering an ideal user experience by precisely predicting network variations and rapidly adapting to available bandwidth, minimizing rebuffering events and bitrate level changes.     

Multiple-server movie-retrieval strategies for distributed multimedia applications: a play-while-retrieve approach

In this paper, we present a generalized approach to retrieve a long-duration movie requested using a network-based video-on-demand service infrastructure employing multiple servers. We design and analyze a play-while-retrieve (PWR) playback strategy for this multiserver environment such that the access time (waiting time for the clients) is minimized. For this strategy, we use both the single-installment and multi-installment retrieval strategies to analyze the performance of the service system. For the above-mentioned retrieval strategies, we explicitly derive closed-form expressions for a minimum access time. For the case of multi-installment retrieval strategy, we conduct asymptotic performance analysis that quantifies the ultimate performance bounds of our strategy. We demonstrate analytically the impact of a large-scale network, as well as the impact of indefinitely increasing the number of installments, on the performance of such a multiserver service system. We then address the problem of buffer management at the client site, which is a closely related issue that has a significant influence on the performance of the strategy, and also serves as a key issue in making the service system attractive for clients. We derive relationships that quantify the minimum amount of buffer expected at the client site to have a smooth presentation with this multiserver service structure. Finally, we perform simulation experiments to verify all our theoretical findings. In the experiments, we compare the performance of PWR strategy with that of play-after-retrieve strategy, and discuss certain important points that are crucial for implementing a real-life working multiserver service system.     

Adaptive Broadcasting for Similarity Queries in Wireless Content Delivery Systems

We present a new adaptive and energy-efficient broadcast dissemination model that supports flexible responses to client requests. In current broadcast dissemination models, clients must specify precisely what documents they require, and servers disseminate exactly those documents. This approach can be impractical, since in practice, clients may know the characteristics of the documents, but not the document names or IDs. In our model, clients specify the required document using attributes, and servers broadcast documents that match client requests at a prespecified level of similarity. A single document may satisfy several clients, so the server broadcasts a minimal set of documents that achieves a desired level of satisfaction in the client population. We introduce a mechanism for the server to obtain randomized feedback from clients to adapt its broadcast program to client needs. Finally, the server integrates a selective tune-in scheme based on approximate index matching to allow clients to conserve energy. Our simulation results show that our model captures client interest patterns efficiently and accurately and scales very well with the number of clients, while reducing overall client average waiting times. The selective tune-in scheme can considerably reduce the consumption of client energy with moderate waiting time overhead.     

Super-Streaming: A New Object Delivery Paradigm for Continuous Media Servers

A number of studies have focused on the design of continuous media, CM, (e.g., video and audio) servers to support the real-time delivery of CM objects. These systems have been deployed in local environments such as hotels, hospitals and cruise ships to support media-on-demand applications. They typically stream CM objects to the clients with the objective of minimizing the buffer space required at the client site. This objective can now be relaxed due to the availability of inexpensive storage devices at the client side. Therefore, we propose a Super-streaming paradigm that can utilize the client side resources in order to improve the utilization of the CM server. To support super-streaming, we propose a technique to enable the CM servers to deliver CM objects at a rate higher than their display bandwidth requirement. We also propose alternative admission control policies to downgrade super-streams in favor of regular streams when the resources are scarce. We demonstrate the superiority of our paradigm over streaming with both analytical and simulation models.Moreover, new distributed applications such as distant-learning, digital libraries, and home entertainment require the delivery of CM objects to geographically disbursed clients. For quality purposes, recently many studies proposed dedicated distributed architectures to support these types of applications. We extend our super-streaming paradigm to be applicable in such distributed architectures. We propose a sophisticated resource management policy to support super-streaming in the presence of multiple servers, network links and clients. Due to the complexity involved in modeling these architectures, we only evaluate the performance of super-streaming by a simulation study.     

Channel Allocation under Batching and VCR Control in Video-on-Demand Systems

In order to guarantee continuous delivery of a video stream in an on-demand video server environment, a collection of resources (referred to as a logical channel) are reserved in advance. To conserve server resources, multiple client requests for the same video can be batched together and served by a single channel. Increasing the window over which all requests for a particular video are batched results in larger savings in server capacity; however, it also increases the reneging probability of a client. A complication introduced by batching is that if a batched client pauses, a new stream (which may not be immediately available) needs to be started when the client resumes. To provide short response time to resume requests, some channels are set aside and are referred to as contingency channels. To further improve resource utilization, even when a nonbatched client pauses, the channel is released and reacquired upon resume. In this paper, we first develop an analytical model that predicts the reneging probability and expected resume delay, and then use this model to optimally allocate channels for batching, on-demand playback, and contingency. The effectiveness of the proposed policy over a scheme with no contingency channels and no batching is also demonstrated.     

A cost-efficient method for streaming stored content in a guaranteed QoS Internet

Quality-of-service techniques allow network providers to differentiate the services they offer to their customers. This differentiation makes it possible to consider charging new quality transport services based on network resource usage. In a content streaming framework, consumers pay for content and network access. Similarly, content providers pay to reserve transport service resources to deliver high-quality content. Therefore, content providers need new cost-efficient methods that optimize network resource reservations. Our paper proposes a new method that ensures data availability on the client side while optimizing network resource reservation when servers deliver stored content with semi-elastic unicast flows. The method uses network resource reservation to guarantee the delivery rate when stored data is below a minimum threshold in the client memory. When occupancy reaches a maximum threshold, the transmission changes to the classic best-effort service, which is not charged based on usage but at a flat rate. The proper design of these thresholds optimizes transmission cost. We validate our analytical method using the ns-2 simulator. We also present a new approach for improving this method when the best-effort delivery rate from the server to the client presents higher variability. Finally, we analyse the case of several homogeneous clients that simultaneously require resource reservation from the server. To avoid resource reservation rejection in the server, bandwidth must be suitably allocated among the clients. To evaluate this more complex case, we also perform some simulations and implement the associated prototype to validate the simulations. The qualitative simulation results reveal optimum working areas in which usage-cost reduction efficiency of the method is significant and extra signalling is minimum.     

Incremental View Maintenance for Mobile Databases

In a mobile environment, querying a database at a stationary server from a mobile client is expensive due to the limited bandwidth of a wireless channel and the instability of the wireless network. We address this problem by maintaining a materialized view in a mobile client's local storage. Such a materialized view can be considered as a data warehouse. The materialized view contains results of common queries in which the mobile client is interested. In this paper, we address the view update problem for maintaining the consistency between a materialized view at a mobile client and the database server. The content of a materialized view could become incoherent with that at the database server when the content of the database server and/or when the location of the client is changed. Existing view update mechanisms are ‘push-based’. The server is responsible for notifying all clients whose views might be affected by the changes in database or the mobility of the client. This is not appropriate in a mobile environment due to the frequent wireless channel disconnection. Furthermore, it is not easy for a server to keep track of client movements to update individual client location-dependent views. We propose a ‘pull-based’ approach that allows a materialized view to be updated at a client in an incremental manner, requiring a client to request changes to its view from the server. We demonstrate the feasibility of our approach with experimental results. Received 27 January 1999 / Revised 26 November 1999 / Accepted 17 April 2000     

基于C/S的计算在颗粒运动仿真中的应用研究

该文介绍了一个基于服务器和客户机分布式计算的颗粒运动仿真系统。在仿真实验中，单机系统无法满足仿真的各项指标要求，特别是用户交互的响应速度。针对各个仿真模块的特点，按功能特性将其分布到客户机和服务器上。基于空间数据分割和对相邻区粒子的预测，大大地减少了任务重新分配时客户机和服务器之间的通信。在局域网上，实现了客户机和服务器的互联和管理。实验表明。仿真实验的计算效率等得到了提高，提高了系统的人机交互响应速度。     

Using Java applets and CORBA for multi-user distributedapplications

The Java language environment, World Wide Web, and Common Object Request Broker Architecture are complementary software technologies, which when used together provide a powerful set of tools for developing and deploying multi-user distributed applications. We describe an approach to building reasonably sophisticated and easy-to-use client software as WWW-downloadable Java applets, which use CORBA to interact effectively with remote server software and thus coordinate and control access to a set of shared resources. We used this approach to reimplement a portion of an existing multi-user distributed application that had been built using the WWW Common Gateway Interface (CGI), then evaluated the differences between the two approaches. We found our method of combining Java applets and CORBA not only practical but in many ways superior to the widely used CGI approach, as well as to a conventional CORBA approach that does not exploit the WWW     

Risk assessment in service provider communities

Online service delivery undertaken between clients and service providers often incurs risks for both the client and the provider, especially when such an exchange takes place in the context of an electronic service market. For the client, the risk involves determining whether the requested service will be delivered on time and based on the previously agreed Service Level Agreement (SLA). Often risk to the client can be mitigated through the use of a penalty clause in an SLA. For the provider, the risk revolves around ensuring that the client will pay the advertised price and more importantly whether the provider will be able to deliver the advertised service to not incur the penalty identified in the SLA. This becomes more significant when the service providers outsource the actual enactment/execution to a data centre — a trend that has become dominant in recent years, with the emergence of infrastructure providers such as Amazon. In this work we investigate the notion of “risk” from a variety of different perspectives and demonstrate how risk to a service owner (who uses an external, third party data centre for service hosting) can be managed more effectively. A simulation based approach is used to validate our findings.