Optimal methods for coordinated en-route web caching for tree networks

Web caching is an important technology for improving the scalability of Web services. One of the key problems in coordinated enroute Web caching is to compute the locations for storing copies of an object among the enroute caches so that some specified objectives are achieved. In this article, we address this problem for tree networks, and formulate it as a maximization problem. We consider this problem for both unconstrained and constrained cases. The constrained case includes constraints on the cost gain per node and on the number of object copies to be placed. We present dynamic programming-based solutions to this problem for different cases and theoretically show that the solutions are either optimal or convergent to optimal solutions. We derive efficient algorithms that produce these solutions. Based on our mathematical model, we also present a solution to coordinated enroute Web caching for autonomous systems as a natural extension of the solution for tree networks. We implement our algorithms and evaluate our model on different performance metrics through extensive simulation experiments. The implementation results show that our methods outperform the existing algorithms of either coordinated enroute Web caching for linear topology or object placement (replacement) at individual nodes only.Keqiu Li, Hong Shen, Francis Y. L. Chin, Si Qing Zhen

An O(nh) algorithm for dual-server coordinated en-route caching in tree networks

Dual-server coordinated en-route caching is important because of its basic features as multi-server en-route caching. In this paper, multi-server coordinated en-route caching is formulated as an optimization problem of minimizing total access cost, including transmission cost for all access demands and caching cost of all caches. We first discuss an algorithm for single-server en-route caching in tree networks and then show that this is a special case of another algorithm for dual-server en-route caching in tree networks whose time complexity is O(nh).Shihong Xu, Hong She

Online algorithms for content caching: an economic perspective

Content Caching at intermediate nodes, such that future requests can be served without going back to the origin of the content, is an effective way to optimize the operations of computer networks. Therefore, content caching reduces the delivery delay and improves the users’ Quality of Experience (QoE). The current literature either proposes offline algorithms that have complete knowledge of the request profile a priori, or proposes heuristics without provable performance. In this dissertation, online algorithms are presented for content caching in three different network settings: the current Internet Network, collaborative multi-cell coordinated network, and future Content Centric Networks (CCN). Due to the difficulty of obtaining a prior knowledge of contents’ popularities in real scenarios, an algorithm has to make a decision whether to cache a content or not when a request for the content is made, and without the knowledge of any future requests. The performance of the online algorithms is measured through a competitive ratio analysis, comparing the performance of the online algorithm to that of an omniscient optimal offline algorithm. Through theoretical analyses, it is shown that the proposed online algorithms achieve either the optimal or close to the optimal competitive ratio. Moreover, the algorithms have low complexity and can be implemented in a distributed way. The theoretical analyses are complemented with simulation-based experiments, and it is shown that the online algorithms have better performance compared to the state of the art caching schemes

Enhanced Cuckoo Search Algorithm for Virtual Machine Placement in Cloud Data Centers

In order to enhance resource utilisation and power efficiency in cloud data centres it is important to perform Virtual Machine (VM) placement in an optimal manner. VM placement uses the method of mapping virtual machines to physical machines (PM). Cloud computing researchers have recently introduced various meta-heuristic algorithms for VM placement considering the optimised energy consumption. However, these algorithms do not meet the optimal energy consumption requirements. This paper proposes an Enhanced Cuckoo Search (ECS) algorithm to address the issues with VM placement focusing on the energy consumption. The performance of the proposed algorithm is evaluated using three different workloads in CloudSim tool. The evaluation process includes comparison of the proposed algorithm against the existing Genetic Algorithm (GA), Optimised Firefly Search (OFS) algorithm, and Ant Colony (AC) algorithm. The comparision results illustrate that the proposed ECS algorithm consumes less energy than the participant algorithms while maintaining a steady performance for SLA and VM migration. The ECS algorithm consumes around 25% less energy than GA, 27% less than OFS, and 26% less than AC

CACHE MANAGEMENT ALGORITHMS: SINGLE AND NETWORKED CACHES

Ph.DDOCTOR OF PHILOSOPH

Exploiting the power of multiplicity: a holistic survey of network-layer multipath

The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work

Content, Topology and Cooperation in In-network Caching

In-network caching aims at improving content delivery and alleviating pressures on network bandwidth by leveraging universally networked caches. This thesis studies the design of cooperative in-network caching strategy from three perspectives: content, topology and cooperation, specifically focuses on the mechanisms of content delivery and cooperation policy and their impacts on the performance of cache networks. The main contributions of this thesis are twofold. From measurement perspective, we show that the conventional metric hit rate is not sufficient in evaluating a caching strategy on non-trivial topologies, therefore we introduce footprint reduction and coupling factor, which contain richer information. We show cooperation policy is the key in balancing various tradeoffs in caching strategy design, and further investigate the performance impact from content per se via different chunking schemes. From design perspective, we first show different caching heuristics and smart routing schemes can significantly improve the caching performance and facilitate content delivery. We then incorporate well-defined fairness metric into design and derive the unique optimal caching solution on the Pareto boundary with bargaining game framework. In addition, our study on the functional relationship between cooperation overhead and neighborhood size indicates collaboration should be constrained in a small neighborhood due to its cost growing exponentially on general network topologies.Verkonsisäinen välimuistitallennus pyrkii parantamaan sisällöntoimitusta ja helpottamaan painetta verkon siirtonopeudessa hyödyntämällä universaaleja verkottuneita välimuisteja. Tämä väitöskirja tutkii yhteistoiminnallisen verkonsisäisen välimuistitallennuksen suunnittelua kolmesta näkökulmasta: sisällön, topologian ja yhteistyön kautta, erityisesti keskittyen sisällöntoimituksen mekanismeihin ja yhteistyökäytäntöihin sekä näiden vaikutuksiin välimuistiverkkojen performanssiin. Väitöskirjan suurimmat aikaansaannokset ovat kahdella saralla. Mittaamisen näkökulmasta näytämme, että perinteinen metrinen välimuistin osumatarkkuus ei ole riittävä ei-triviaalin välimuistitallennusstrategian arvioinnissa, joten esittelemme parempaa informaatiota sisältävät jalanjäljen pienentämisen sekä yhdistämistekijän. Näytämme, että yhteistyökäytäntö on avain erilaisten välimuistitallennusstrategian suunnitteluun liittyvien kompromissien tasapainotukseen ja tutkimme lisää sisällön erilaisten lohkomisjärjestelmien kautta aiheuttamaa vaikutusta performanssiin. Suunnittelun näkökulmasta näytämme ensin, kuinka erilaiset välimuistitallennuksen heuristiikat ja viisaan reitityksen järjestelmät parantavat merkittävästi välimuistitallennusperformanssia sekä helpottavat sisällön toimitusta. Sisällytämme sitten suunnitteluun hyvin määritellyn oikeudenmukaisuusmittarin ja johdamme uniikin optimaalin välimuistitallennusratkaisun Pareto-rintamalla neuvottelupelin kehyksissä. Lisäksi tutkimuksemme yhteistyökustannusten ja naapurustokoon funktionaalisesta suhteesta viittaa siihen, että yhteistyö on syytä rajoittaa pieneen naapurustoon sen kustannusten kasvaessa eksponentiaalisesti yleisessä verkkotopologiassa

Rich media content adaptation in e-learning systems

The wide use of e-technologies represents a great opportunity for underserved segments of the population, especially with the aim of reintegrating excluded individuals back into society through education. This is particularly true for people with different types of disabilities who may have difficulties while attending traditional on-site learning programs that are typically based on printed learning resources. The creation and provision of accessible e-learning contents may therefore become a key factor in enabling people with different access needs to enjoy quality learning experiences and services. Another e-learning challenge is represented by m-learning (which stands for mobile learning), which is emerging as a consequence of mobile terminals diffusion and provides the opportunity to browse didactical materials everywhere, outside places that are traditionally devoted to education. Both such situations share the need to access materials in limited conditions and collide with the growing use of rich media in didactical contents, which are designed to be enjoyed without any restriction. Nowadays, Web-based teaching makes great use of multimedia technologies, ranging from Flash animations to prerecorded video-lectures. Rich media in e-learning can offer significant potential in enhancing the learning environment, through helping to increase access to education, enhance the learning experience and support multiple learning styles. Moreover, they can often be used to improve the structure of Web-based courses. These highly variegated and structured contents may significantly improve the quality and the effectiveness of educational activities for learners. For example, rich media contents allow us to describe complex concepts and process flows. Audio and video elements may be utilized to add a “human touch” to distance-learning courses. Finally, real lectures may be recorded and distributed to integrate or enrich on line materials. A confirmation of the advantages of these approaches can be seen in the exponential growth of video-lecture availability on the net, due to the ease of recording and delivering activities which take place in a traditional classroom. Furthermore, the wide use of assistive technologies for learners with disabilities injects new life into e-learning systems. E-learning allows distance and flexible educational activities, thus helping disabled learners to access resources which would otherwise present significant barriers for them. For instance, students with visual impairments have difficulties in reading traditional visual materials, deaf learners have trouble in following traditional (spoken) lectures, people with motion disabilities have problems in attending on-site programs. As already mentioned, the use of wireless technologies and pervasive computing may really enhance the educational learner experience by offering mobile e-learning services that can be accessed by handheld devices. This new paradigm of educational content distribution maximizes the benefits for learners since it enables users to overcome constraints imposed by the surrounding environment. While certainly helpful for users without disabilities, we believe that the use of newmobile technologies may also become a fundamental tool for impaired learners, since it frees them from sitting in front of a PC. In this way, educational activities can be enjoyed by all the users, without hindrance, thus increasing the social inclusion of non-typical learners. While the provision of fully accessible and portable video-lectures may be extremely useful for students, it is widely recognized that structuring and managing rich media contents for mobile learning services are complex and expensive tasks. Indeed, major difficulties originate from the basic need to provide a textual equivalent for each media resource composing a rich media Learning Object (LO). Moreover, tests need to be carried out to establish whether a given LO is fully accessible to all kinds of learners. Unfortunately, both these tasks are truly time-consuming processes, depending on the type of contents the teacher is writing and on the authoring tool he/she is using. Due to these difficulties, online LOs are often distributed as partially accessible or totally inaccessible content. Bearing this in mind, this thesis aims to discuss the key issues of a system we have developed to deliver accessible, customized or nomadic learning experiences to learners with different access needs and skills. To reduce the risk of excluding users with particular access capabilities, our system exploits Learning Objects (LOs) which are dynamically adapted and transcoded based on the specific needs of non-typical users and on the barriers that they can encounter in the environment. The basic idea is to dynamically adapt contents, by selecting them from a set of media resources packaged in SCORM-compliant LOs and stored in a self-adapting format. The system schedules and orchestrates a set of transcoding processes based on specific learner needs, so as to produce a customized LO that can be fully enjoyed by any (impaired or mobile) student

Decision-Theoretic Meta-reasoning in Partially Observable and Decentralized Settings

This thesis examines decentralized meta-reasoning. For a single agent or multiple agents, it may not be enough for agents to compute correct decisions if they do not do so in a timely or resource efficient fashion. The utility of agent decisions typically increases with decision quality, but decreases with computation time. The reasoning about one\u27s computation process is referred to as meta-reasoning. Aspects of meta-reasoning considered in this thesis include the reasoning about how to allocate computational resources, including when to stop one type of computation and begin another, and when to stop all computation and report an answer. Given a computational model, this translates into computing how to schedule the basic computations that solve a problem. This thesis constructs meta-reasoning strategies for the purposes of monitoring and control in multi-agent settings, specifically settings that can be modeled by the Decentralized Partially Observable Markov Decision Process (Dec-POMDP). It uses decision theory to optimize computation for efficiency in time and space in communicative and non-communicative decentralized settings. Whereas base-level reasoning describes the optimization of actual agent behaviors, the meta-reasoning strategies produced by this thesis dynamically optimize the computational resources which lead to the selection of base-level behaviors