The prevalence of smart wearable devices is increasing exponentially and we are witnessing a wide variety of fascinating new services that leverage the capabilities of these wearables. Wearables are truly changing the way mobile computing is deployed and mobile apps are being developed. It is possible to leverage the capabilities such as connectivity, processing, and sensing of wearable devices in an adaptive manner for efficient resource usage and information accuracy within the personal area network. We show that app developers are not yet taking advantage of these cross-device capabilities, however, instead using wearables as passive sensors or simple end displays to provide notifications to the user. We thus design Application Function Virtualization (AFV), an architecture enabling automated dynamic function virtualization and scheduling across devices in a personal area network, simplifying the development of the apps that are adaptive to context changes. AFV provides a simple set of APIs hiding complex architectural tasks from app developers whilst continuously monitoring the user, device, and network context, to enable the adaptive invocation of functions across devices. We show the feasibility of our design by implementing AFV on Android, and the benefits for the user in terms of resource efficiency, especially in saving energy consumption, and quality of experience with multiple use cases.

Hierarchical caching enables users to obtain content from one of (possibly) many caches between an edge router cache and an origin server, reducing latency/overall network traffic. This can be used in many network architectures, including P2P networks and Content Distribution Networks. Of particular interest are Information Centric Networks (ICNs), which decouple content identifiers from specific network hosts and explicitly consider universal caching (collaboration between network routers) as a desirable feature.Performance analysis of a large-scale hierarchy of caches requires accurate mathematical models for various cache replacement algorithms. There is no previous study that models LRU-k. This cache replacement algorithm is important since its principle is the basis of recent algorithms such as k-LRU that outperform LRU in many situations. We first model LRU-2 using Che's approximation, as a specific case of LRU-k for k=2. We also extend our model to a hierarchical network of LRU-2 caches. The model is validated analytically and with simulation. The experiments show that the proposed model approximates LRU-2 accurately. LRU-2 and 2-LRU are also compared analytically and with simulations. The comparison between the two algorithms illustrates that 2-LRU outperforms LRU-2.

The majority of available wearable computing devices require communication with Internet servers for data analysis and storage, and rely on a paired smartphone to enable secure communication. However, many wearables are equipped with WiFi network interfaces, enabling direct communication with the Internet. Secure communication protocols could then run on these wearables themselves, yet it is not clear if they can be efficiently supported.,,,,In this paper, we show that wearables are ready for direct and secure Internet communication by means of experiments with both controlled local web servers and Internet servers. We observe that the overall energy consumption and communication delay can be reduced with direct Internet connection via WiFi from wearables compared to using smartphones as relays via Bluetooth. We also show that the additional HTTPS cost caused by TLS handshake and encryption is closely related to the number of parallel connections, and has the same relative impact on wearables and smartphones.

The current Internet architecture follows a hostcentric communication model, intended for machine to machine connection and message passing. Modern Internet users are mainly interested in accessing information by name, irrespective of physical location. Information centric networking (ICN) was developed to rethink Internet foundations. Innetwork caching is one of the main features of ICN. Studying the performance of different caching algorithms in ICN requires a good understanding of users' request distributions in such networks. Most studies use simplifying assumptions for user request patterns since ICNs are not yet deployed. Geographically localized and global request patterns have both been observed to possess Zipf-like properties, although the local distributions are poorly correlated with the global distribution. Several independent Zipf distributions combine to form an emergent Zipf distribution in real client request scenarios. We develop an algorithm that can generate realistic synthetic traffic for geographic regions that possesses Zipf power-law properties as well as a global Zipf distribution. Our simulation results show that the caching performance would have different behaviour based on users' requests distribution.

Smart wearable devices are widely available today and changing the way mobile applications are being developed. Applications can dynamically leverage the capabilities of wearable devices worn by the user for optimal resource usage and information accuracy, depending on the user/device context and application requirements. However, application developers are not yet taking advantage of these cross-device capabilities.

Sensor devices and the emergent networks that they enable are capable of transmitting information between data sources.Since these devices have low-power and intermittent connectivity, latency of delivery for certain classes of data may be tolerated in an effort to save energy. The BUBBLE routing algorithm, proposed by Hui it et al., provides consistent routing, employing a model which considers the popularity of individual nodes within communities and only passes messages to nodes with higher probability of delivery. We have developed an improvement to BUBBLE, called Community-Based-Forwarding (CBF) that considers the interactions between communities as an additional factor in message forwarding. By using community information, CBF is able to exploit intermediate connections between clusters to route messages with more balanced node participation and higher levels of reliability and efficiency.

Real-time distributed groupware sends several kinds of messages with varying quality-of-service requirements. However, standard network protocols do not provide the flexibility needed to support these different requirements (either providing too much reliability or too little), leading to poor performance on real-world networks. To address this problem, we investigated the use of an application-level networking technique called adaptive forward error correction (AFEC) for real-time groupware. AFEC can maintain a predefined level of reliability while avoiding the overhead of packet acknowledgement or retransmission. We analysed the requirements of typical real-time groupware systems and developed an AFEC technique to meet these needs. We tested the new technique in an experiment that measured message reliability and latency using TCP, plain UDP, UDP with non-adaptive FEC, and UDP with our AFEC scheme, under several simulated network conditions. Our results show that for awareness messages that can tolerate some loss, FEC approaches keep latency at nearly the plain-UDP level while dramatically improving reliability. In addition, adaptive FEC is the only technique that can maintain a specified level of reliability and also minimize delay as network conditions change. Our study shows that groupware AFEC can be a useful tool for improving the real-world performance and usability of real-time groupware.

A modern twist to clock synchronization is the push towards server virtualization and cloud computing. Distributed applications now often run on geographically-distributed, virtualized servers that are isolated from the underlying hardware. Despite the fact that most applications run well in an abstracted environment without direct hardware access, tight real-time synchronized clocks are still necessary. We performed a set of experiments to quantify the additional clock error when running the NTP daemon inside a Virtual Machine. We found that the delay asymmetry is relatively small when running in a non-virtualized environment, but quite significant in a virtualized environment.

Modern web applications consist of many distinct services that collaborate to provide the full application functionality. To improve application performance, developers need to be able to identify the root cause of performance problems; identifying and fixing performance problems in these distributed, heterogeneous applications can be very difficult. As web applications become more complicated, the number of systems involved will continue to grow and full-system performance tuning will become more difficult.

Sensor networks are often deployed more densely than would be minimally required. In such cases, node scheduling protocols can be used to determine which nodes are active, and which nodes sleep so as to conserve energy and prolong network lifetime. A drawback of node scheduling approaches, however, is delay due to node or communication failure(s), and subsequent wake-up of replacement node(s), during which monitoring coverage of some sub-region may be lost. This paper proposes an alternative approach for use in contexts in which the objective is to periodically collect sensing data that completely covers a region of interest. In the proposed approach, nodes dynamically determine during each round of data collection whether they should transmit their data, or whether their area is covered by neighbouring nodes that have already transmitted. Both unicast and broadcast-based data collection protocols are designed, and their performance compared using simulation to that of data collection protocols relying on node scheduling. Our results suggest that the coverage-preserving broadcast-based protocol can greatly improve reliability at the potential cost of increased traffic volume owing to non-minimal selection of transmitting nodes.

Capacity planning, as well as protocol design and storage system design for video distribution systems are dependent on an understanding of the anticipated workload. Previous studies have focused on aggregate statistics of video popularity over time, and only recently has work been done which analyzes user behaviour variability over time. We are interested in a video storage/distribution system that uses peer resources to help content providers distribute video content to nodes in a network over long periods of time. Such a system is intended to operate on local principles of utility associated with each peer. More than ever, a workload model based on long-term user behaviour is required. In particular, it is unclear how request patterns driven by local utility can be shaped to match expected large-scale aggregate request characteristics such as a Zipf-distribution for overall popularity. In this paper, we describe early work in developing a workload generator for a Peer-based PVR (Personal Video Recorder) system to demonstrate some of these challenges.

Wireless mesh networks are being increasingly used to provide affordable network connectivity to communities where wired deployment strategies are either not possible or are prohibitively expensive. Unfortunately, computer networks (including mesh networks) are frequently being exploited by increasingly profit-driven and insidious attackers, which can affect their utility for legitimate use. In response to this, a number of countermeasures have been developed, including intrusion detection systems that aim to detect anomalous behaviour caused by attacks. We present a set of socio-technical challenges associated with developing an intrusion detection system for a community wireless mesh network. The attack space on a mesh network is particularly large; we motivate the need for and describe the challenges of adopting an asset-driven approach to managing this space. Finally, we present an initial design of a modular architecture for intrusion detection, highlighting how it addresses the identified challenges.

Video has become an important application for wireless networks as they have become popular for many users and uses. There are challenges delivering video content over a wireless link, both due to the volume of traffic and the high data loss rates experienced. Data loss in compressed media results in errors in the decoded video, and noticeable visual artifacts. These losses can have long-term effects in video display. This paper presents the concept of mixed reliability video streaming (Mixed Streaming), which reduces the impact of video propagation errors in error prone wireless networks. Mixed Streaming delivers a video file using both reliable and best-effort connections. Simulation results show that Mixed Streaming reduces the impact of errors by making sure that errors on reference frames are corrected. Also, the delay cost associated with Mixed Sreaming is reasonable even for fairly high packet loss rates.

One of a Software Engineer's most important skills is the ability to define the scope of the problem and ascertain the requirements from general and vague specifications. Teaching this skill is known to be difficult and is made more complex because students are conditioned to expect that this portion of programming projects is already complete. This paper reports on experience in teaching a second year computer science class which exposed the need for requirements engineering and gave students an opportunity to engage in the activity. We found that the student response was bimodal, and while some students met the challenge, more felt betrayed by the experience. We conclude that students gained the requisite knowledge using this approach but that a less traumatic approach may produce better results.

In an e-commerce system, the database server performance is crucial. Dynamic caching is often used to reduce the load on the database server, which reduces the need for scalability within the server itself. A good understanding of the workload characteristics of the database server in an e-commerce environment is important to the design, tuning, and capacity planning. Using dynamic caching can dramatically alter the characteristics of requests that the database server receives, changing the dominant operations, even the workload type. The two major database workload classifications are online analytical processing and online transaction processing. Allocations for resources such as main memory can be very different, depending on the workload type. We investigate the e-commerce activity profiles resulting from dynamic caching. We find that dynamic caching does tend to alter the behavior towards transaction processing.

Media server software is significantly complicated to develop and maintain, due to the nature of the many interface aspects which must be considered. This paper provides a case study of the design, implementation, and evolution of a continuous media file server. We place emphasis on the evolution of the software and our approach to maintainability. The user interface is a major consideration, even though the server software would appear isolated from that factor. Since continuous media servers must send the raw data to a client application over a network, the protocol considerations, hardware interface, and data storage/retrieval methods are of the paramount importance. In addition, the application programmer's interface to the server facilities has an impact on both the internal design and the performance of such a server. We discuss our experiences and insight into the development of such software products within a small research-based university environment. We experienced two main types of evolutionary change: requirements changes from the limited user community and performance enhancements/corrections. While the former were anticipated via a generic interface and modular design structure, the latter were surprising and substantially more difficult to solve. Copyright © 2005 John Wiley & Sons, Ltd.

In conventional commerce, customer groups with similar interests or behaviours can be observed. Similarly, customers in E-commerce naturally form groups. These groups allow the organization to provide quality of service (QoS) and perform capacity planning. From a system point of view, overall server performance can be improved and resources managed considering customer session behaviour.Previous studies have grouped customers using clustering techniques. Different data metrics have been selected as criteria for grouping, in order to analyze different problems. The limitation for these approaches is that problems areanalyzed separately. In order to manage an E-commerce server well, we must analyze many related problems comprehensively rather than separately. For example, we would like to know what is the impact on resource usage when optimizing revenue. Thus, we must understand the differences and similarities between session groups chosen by different metrics.This paper characterizes customer groups for an E-rental business and compares customer groups created according to different criteria including services requested, navigation pattern and resource usage. A significant finding of this study shows that using each of the three criteria independently yields roughly similar results, since customers looking for similar services tend to have similar navigation pattern as well as similar server resource usage. Thus, it issufficient to group customers in only one of these ways. Grouping customers by services requested is suggested since this method yields relatively better results and is simple to implement.

Abstract A file server for continuous media must provide resource guarantees and only admit requests that do not violate the resource availability. This paper addresses the admission performance of a server that explicitly considers the variable bit rate nature of the continuous media streams. A prototype version of the server has been implemented and evaluated in several heterogeneous environments. The two system resources for which admission control is evaluated are the disk bandwidth and the network bandwidth. Performance results from both measurement and simulation are shown with respect to different admission methods and varying scenarios of stream delivery patterns. We show that the vbrSim algorithm developed specifically for the server outperforms the other options for disk admission especially with request patterns that have staggered arrivals, while the network admission control algorithm is able to utilize a large percentage of the network bandwidth available. We also show the interactions between the limits of these two resources and how a system can be configured without wasted capacity on either one of the resources. Copyright © 2004 John Wiley & Sons, Ltd.

We describe the design and implementation of a file server for variable bit rate continuous media. We address the problem of building a server where each stream may have a different bit rate and, more importantly, where the bit rate within a single stream may vary considerably. Such a server has been implemented within a high-speed network environment. The server is designed to be used in a heterogeneous environment and is linearly scalable. A significant aspect of the design of the system is the detailed consideration of the variable bit-rate profile of each data stream in performing admission control for the disk and for the network. This paper describes the system model, the user interface design, implementation details, and performance results based on initial experience with the server.

In this paper, we address the problem of choosing a disk admission algorithm for continuous media streams where each stream may have a different bit rate, and more importantly, where the bit rate within a single stream may vary considerably.We evaluate several different Variable Bit Rate (VBR) disk admission control algorithms for continuous media.An algorithm which accepts too few streams under-utilizes the server resources, while an algorithm which accepts too many streams over-utilizes the resources resulting in inadequate service (i.e.missing or delayed data) to the clients.The evaluation process is based on a representative set of video streams encoded in MJPEG.We conclude that one particular algorithm, the VBR simulation algorithm, performs the best among realizable algorithms in terms of system utilization and delivery guarantees and performs close to an optimal algorithm, Keywords: multimedia, file servers, variable bit rate, admission control Pemhsion to mnke digitnhrd topics orall or part ofthis mnterinl for personal or clnssroom use is granted without Ike provided IIXII the copi& are not mnde or distribtltrd for prolit or coonuncrcinl advantage.11x copy-

The influence of client and server cache sizes and the number of clients on caching performance is studied through trace-driven simulation. The results indicate that the locality of reference in disk block reference patterns allows relatively small caches to reduce significantly the number of disk accesses required. File server cache performance is significantly different from client cache performance owing to the capture of disk block references by the client caches. The major factor influencing overall miss ratio statistics (actual disk reference frequencies) is found to be the maximum of the server cache size and the size of client caches.>