CATS: linearizability and partition tolerance in scalable and self-organizing key-value stores

Distributed key-value stores provide scalable, fault-tolerant, and self-organizing storage services, but fall short of guaranteeing linearizable consistency in partially synchronous, lossy, partitionable, and dynamic networks, when data is distributed and replicated automatically by the principle of consistent hashing. This paper introduces consistent quorums as a solution for achieving atomic consistency. We present the design and implementation of CATS, a distributed key-value store which uses consistent quorums to guarantee linearizability and partition tolerance in such adverse and dynamic network conditions. CATS is scalable, elastic, and self-organizing; key properties for modern cloud storage middleware. Our system shows that consistency can be achieved with practical performance and modest throughput overhead (5%) for read-intensive workloads

An adaptive admission control and load balancing algorithm for a QoS-aware Web system

The main objective of this thesis focuses on the design of an adaptive algorithm for admission control and content-aware load balancing for Web traffic. In order to set the context of this work, several reviews are included to introduce the reader in the background concepts of Web load balancing, admission control and the Internet traffic characteristics that may affect the good performance of a Web site. The admission control and load balancing algorithm described in this thesis manages the distribution of traffic to a Web cluster based on QoS requirements. The goal of the proposed scheduling algorithm is to avoid situations in which the system provides a lower performance than desired due to servers' congestion. This is achieved through the implementation of forecasting calculations. Obviously, the increase of the computational cost of the algorithm results in some overhead. This is the reason for designing an adaptive time slot scheduling that sets the execution times of the algorithm depending on the burstiness that is arriving to the system. Therefore, the predictive scheduling algorithm proposed includes an adaptive overhead control. Once defined the scheduling of the algorithm, we design the admission control module based on throughput predictions. The results obtained by several throughput predictors are compared and one of them is selected to be included in our algorithm. The utilisation level that the Web servers will have in the near future is also forecasted and reserved for each service depending on the Service Level Agreement (SLA). Our load balancing strategy is based on a classical policy. Hence, a comparison of several classical load balancing policies is also included in order to know which of them better fits our algorithm. A simulation model has been designed to obtain the results presented in this thesis

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

Adaptive Load Balancing Policy for Web Server Custer

The paper highlights the significance of open source software for distributed computing environment and proposes an adaptive load balancing model using open source software for distributed computing environment. The load balancing strategies used by the model are based on load of the system. The proposed algorithm uses current load, response ratio and processor utilization of the nodes of the web server cluster to evaluate the performance

Cache Serializability: Reducing Inconsistency in Edge Transactions

Read-only caches are widely used in cloud infrastructures to reduce access latency and load on backend databases. Operators view coherent caches as impractical at genuinely large scale and many client-facing caches are updated in an asynchronous manner with best-effort pipelines. Existing solutions that support cache consistency are inapplicable to this scenario since they require a round trip to the database on every cache transaction. Existing incoherent cache technologies are oblivious to transactional data access, even if the backend database supports transactions. We propose T-Cache, a novel caching policy for read-only transactions in which inconsistency is tolerable (won't cause safety violations) but undesirable (has a cost). T-Cache improves cache consistency despite asynchronous and unreliable communication between the cache and the database. We define cache-serializability, a variant of serializability that is suitable for incoherent caches, and prove that with unbounded resources T-Cache implements this new specification. With limited resources, T-Cache allows the system manager to choose a trade-off between performance and consistency. Our evaluation shows that T-Cache detects many inconsistencies with only nominal overhead. We use synthetic workloads to demonstrate the efficacy of T-Cache when data accesses are clustered and its adaptive reaction to workload changes. With workloads based on the real-world topologies, T-Cache detects 43-70% of the inconsistencies and increases the rate of consistent transactions by 33-58%.Comment: Ittay Eyal, Ken Birman, Robbert van Renesse, "Cache Serializability: Reducing Inconsistency in Edge Transactions," Distributed Computing Systems (ICDCS), IEEE 35th International Conference on, June~29 2015--July~2 201

Using real options to select stable Middleware-induced software architectures

The requirements that force decisions towards building distributed system architectures are usually of a non-functional nature. Scalability, openness, heterogeneity, and fault-tolerance are examples of such non-functional requirements. The current trend is to build distributed systems with middleware, which provide the application developer with primitives for managing the complexity of distribution, system resources, and for realising many of the non-functional requirements. As non-functional requirements evolve, the `coupling' between the middleware and architecture becomes the focal point for understanding the stability of the distributed software system architecture in the face of change. It is hypothesised that the choice of a stable distributed software architecture depends on the choice of the underlying middleware and its flexibility in responding to future changes in non-functional requirements. Drawing on a case study that adequately represents a medium-size component-based distributed architecture, it is reported how a likely future change in scalability could impact the architectural structure of two versions, each induced with a distinct middleware: one with CORBA and the other with J2EE. An option-based model is derived to value the flexibility of the induced-architectures and to guide the selection. The hypothesis is verified to be true for the given change. The paper concludes with some observations that could stimulate future research in the area of relating requirements to software architectures