Growth of relational model: Interdependence and complementary to big data

A database management system is a constant application of science that provides a platform for the creation, movement, and use of voluminous data. The area has witnessed a series of developments and technological advancements from its conventional structured database to the recent buzzword, bigdata. This paper aims to provide a complete model of a relational database that is still being widely used because of its well known ACID properties namely, atomicity, consistency, integrity and durability. Specifically, the objective of this paper is to highlight the adoption of relational model approaches by bigdata techniques. Towards addressing the reason for this in corporation, this paper qualitatively studied the advancements done over a while on the relational data model. First, the variations in the data storage layout are illustrated based on the needs of the application. Second, quick data retrieval techniques like indexing, query processing and concurrency control methods are revealed. The paper provides vital insights to appraise the efficiency of the structured database in the unstructured environment, particularly when both consistency and scalability become an issue in the working of the hybrid transactional and analytical database management system

The distributed ASCI supercomputer project

The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Transactional concurrency control for resource constrained applications

PhD ThesisTransactions have long been used as a mechanism for ensuring the consistency of databases. Databases, and associated transactional approaches, have always been an active area of research as different application domains and computing architectures have placed ever more elaborate requirements on shared data access. As transactions typically provide consistency at the expense of timeliness (abort/retry) and resource (duplicate shared data and locking), there has been substantial efforts to limit these two aspects of transactions while still satisfying application requirements. In environments where clients are geographically distant from a database the consistency/performance trade-off becomes acute as any retrieval of data over a network is not only expensive, but relatively slow compared to co-located client/database systems. Furthermore, for battery powered clients the increased overhead of transactions can also be viewed as a significant power overhead. However, for all their drawbacks transactions do provide the data consistency that is a requirement for many application types. In this Thesis we explore the solution space related to timely transactional systems for remote clients and centralised databases with a focus on providing a solution, that, when compared to other's work in this domain: (a) maintains consistency; (b) lowers latency; (c) improves throughput. To achieve this we revisit a technique first developed to decrease disk access times via local caching of state (for aborted transactions) to tackle the problems prevalent in real-time databases. We demonstrate that such a technique (rerun) allows a significant change in the typical structure of a transaction (one never before considered, even in rerun systems). Such a change itself brings significant performance success not only in the traditional rerun local database solution space, but also in the distributed solution space. A byproduct of our improvements also, one can argue, brings about a "greener" solution as less time coupled with improved throughput affords improved battery life for mobile devices

Implementing Infopipes: The SIP/XIP Experiment

We describe an implementation of the Infopipe abstraction for information flow applications. We have implemented software tools that translate the SIP/XIP variant of Infopipe specification into executable code. These tools are evaluated through the rewriting of two realistic applications using Infopipes: a multimedia streaming program and a web source combination application. Measurements show that Infopipe-generated code has the same execution overhead as the manually written original version. Source code of Infopipe version is reduced by 36% to 85% compared to the original

Deterministic Object Management in Large Distributed Systems

Caching is a widely used technique to improve the scalability of distributed systems. A central issue with caching is maintaining object replicas consistent with their master copies. Large distributed systems, such as the Web, typically deploy heuristic-based consistency mechanisms, which increase delay and place extra load on the servers, while not providing guarantees that cached copies served to clients are up-to-date. Server-driven invalidation has been proposed as an approach to strong cache consistency, but it requires servers to keep track of which objects are cached by which clients. We propose an alternative approach to strong cache consistency, called MONARCH, which does not require servers to maintain per-client state. Our approach builds on a few key observations. Large and popular sites, which attract the majority of the traffic, construct their pages from distinct components with various characteristics. Components may have different content types, change characteristics, and semantics. These components are merged together to produce a monolithic page, and the information about their uniqueness is lost. In our view, pages should serve as containers holding distinct objects with heterogeneous type and change characteristics while preserving the boundaries between these objects. Servers compile object characteristics and information about relationships between containers and embedded objects into explicit object management commands. Servers piggyback these commands onto existing request/response traffic so that client caches can use these commands to make object management decisions. The use of explicit content control commands is a deterministic, rather than heuristic, object management mechanism that gives content providers more control over their content. The deterministic object management with strong cache consistency offered by MONARCH allows content providers to make more of their content cacheable. Furthermore, MONARCH enables content providers to expose internal structure of their pages to clients. We evaluated MONARCH using simulations with content collected from real Web sites. The results show that MONARCH provides strong cache consistency for all objects, even for unpredictably changing ones, and incurs smaller byte and message overhead than heuristic policies. The results also show that as the request arrival rate or the number of clients increases, the amount of server state maintained by MONARCH remains the same while the amount of server state incurred by server invalidation mechanisms grows

From Controlled Data-Center Environments to Open Distributed Environments: Scalable, Efficient, and Robust Systems with Extended Functionality

The past two decades have witnessed several paradigm shifts in computing environments. Starting from cloud computing which offers on-demand allocation of storage, network, compute, and memory resources, as well as other services, in a pay-as-you-go billingmodel. Ending with the rise of permissionless blockchain technology, a decentralized computing paradigm with lower trust assumptions and limitless number of participants. Unlike in the cloud, where all the computing resources are owned by some trusted cloud provider, permissionless blockchains allow computing resources owned by possibly malicious parties to join and leave their network without obtaining permission from some centralized trusted authority. Still, in the presence of malicious parties, permissionlessblockchain networks can perform general computations and make progress. Cloud computing is powered by geographically distributed data-centers controlled and managed by trusted cloud service providers and promises theoretically infinite computing resources. On the other hand, permissionless blockchains are powered by open networks of geographically distributed computing nodes owned by entities that are not necessarily known or trusted. This paradigm shift requires a reconsideration of distributed data management protocols and distributed system designs that assume low latency across system components, inelastic computing resources, or fully trusted computing resources.In this dissertation, we propose new system designs and optimizations that address scalability and efficiency of distributed data management systems in cloud environments. We also propose several protocols and new programming paradigms to extend the functionality and enhance the robustness of permissionless blockchains. The work presented spans global-scale transaction processing, large-scale stream processing, atomic transaction processing across permissionless blockchains, and extending the functionality and the use-cases of permissionless blockchains. In all these directions, the focus is on rethinking system and protocol designs to account for novel cloud and permissionless blockchain assumptions. For global-scale transaction processing, we propose GPlacer, a placement optimization framework that decides replica placement of fully and partial geo-replicated databases. For large-scale stream processing, we propose Cache-on-Track (CoT) an adaptive and elastic client-side cache that addresses server-side load-imbalances that occur in large-scale distributed storage layers. In permissionless blockchain transaction processing, we propose AC3WN, the first correct cross-chain commitment protocol that guarantees atomicity of cross-chain transactions. Also, we propose TXSC, a transactional smart contract programming framework. TXSC provides smart contract developers with transaction primitives. These primitives allow developers to write smart contracts without the need to reason about the anomalies that can arise due to concurrent smart contract function executions. In addition, we propose a forward-looking architecture that unifies both permissioned and permissionless blockchains and exploits the running infrastructure of permissionless blockchains to build global asset management systems

Web page performance analysis

Computer systems play an increasingly crucial and ubiquitous role in human endeavour by carrying out or facilitating tasks and providing information and services. How much work these systems can accomplish, within a certain amount of time, using a certain amount of resources, characterises the systems’ performance, which is a major concern when the systems are planned, designed, implemented, deployed, and evolve. As one of the most popular computer systems, the Web is inevitably scrutinised in terms of performance analysis that deals with its speed, capacity, resource utilisation, and availability. Performance analyses for the Web are normally done from the perspective of the Web servers and the underlying network (the Internet). This research, on the other hand, approaches Web performance analysis from the perspective of Web pages. The performance metric of interest here is response time. Response time is studied as an attribute of Web pages, instead of being considered purely a result of network and server conditions. A framework that consists of measurement, modelling, and monitoring (3Ms) of Web pages that revolves around response time is adopted to support the performance analysis activity. The measurement module enables Web page response time to be measured and is used to support the modelling module, which in turn provides references for the monitoring module. The monitoring module estimates response time. The three modules are used in the software development lifecycle to ensure that developed Web pages deliver at worst satisfactory response time (within a maximum acceptable time), or preferably much better response time, thereby maximising the efficiency of the pages. The framework proposes a systematic way to understand response time as it is related to specific characteristics of Web pages and explains how individual Web page response time can be examined and improved