This paper studies the problem of load-balancing the demand for content in a peer-to-peer network across heterogeneous peer nodes that hold replicas of the content. Previous decentralized load balancing techniques in distributed systems base their decisions on periodic updates containing information about load or available capacity observed at the serving entities. We show that these techniques do not work well in the peer-to-peer context; either they do not address peer node heterogeneity, or they suffer from significant load oscillations. We propose a new decentralized algorithm, Max-Cap, based on the maximum inherent capacities of the replica nodes and show that unlike previous algorithms, it is not tied to the timeliness or frequency of updates. Yet, Max-Cap can handle the heterogeneity of a peer-to-peer environment without suffering from load oscillations.
later extend this work to balance load across a set of widely distributed heterogeneous web servers @cite_2 . This work proposes the use of adaptive TTLs, where the TTL for a DNS mapping is set inversely proportional to the domain's local client request rate for the mapping of interest (as reported by the domain's local name server). The TTL is at the same time set to be proportional to the chosen web server's maximum capacity. So web servers with high maximum capacity will have DNS mappings with longer TTLs, and domains with low request rates will receive mappings with longer TTLs. Max-Cap, the algorithm proposed in this thesis, also uses the maximum capacities of the serving replica nodes to allocate requests proportionally. The main difference is that in the work by , the root DNS scheduler acts as a centralized dispatcher setting all DNS mappings and is assumed to know what the request rate in the requesting domain is like. In the peer-to-peer case the authority node has no idea what the request rate throughout the network is like, nor how large is the set of requesting nodes.
@cite_2
1747723070 2168282297 2159285576 2157357672
With ever increasing Web traffic, a distributed multi server Web site can provide scalability and flexibility to cope with growing client demands. Load balancing algorithms to spread the requests across multiple Web servers are crucial to achieve the scalability. Various domain name server (DNS) based schedulers have been proposed in the literature, mainly for multiple homogeneous servers. The presence of heterogeneous Web servers not only increases the complexity of the DNS scheduling problem, but also makes previously proposed algorithms for homogeneous distributed systems not directly applicable. This leads us to propose new policies, cabled adaptive TTL algorithms, that take into account both the uneven distribution of client request rates and heterogeneity of Web servers to adaptively set the time-to-live (TTL) value for each address mapping request. Extensive simulation results show that these strategies are robust and effective in balancing load among geographically distributed heterogeneous Web servers. This paper presents a way of modeling the hit rates of caches that use a time-to-live (TTL)-based consistency policy. TTL-based consistency, as exemplified by DNS and Web caches, is a policy in which a data item, once retrieved, remains valid for a period known as the "time-to-live". Cache systems using large TTL periods are known to have high hit rates and scale well, but the effects of using shorter TTL periods are not well understood. We model hit rate as a function of request arrival times and the choice of TTL, enabling us to better understand cache behavior for shorter TTL periods. Our formula for the hit rate is closed form and relies upon a simplifying assumption about the interarrival times of requests for the data item in question: that these requests can be modeled as a sequence of independent and identically distributed random variables. Analyzing extensive DNS traces, we find that the results of the formula match observed statistics surprisingly well; in particular, the analysis is able to adequately explain the somewhat counterintuitive empirical finding of that the cache hit rate for DNS accesses rapidly increases as a function of TTL, exceeding 80 for a TTL of 15 minutes. Replication of information among multiple World Wide Web servers is necessary to support high request rates to popular Web sites. A clustered Web server organization is preferable to multiple independent mirrored servers because it maintains a single interface to the users and has the potential to be more scalable, fault-tolerant and better load-balanced. In this paper, we propose a Web cluster architecture in which the Domain Name System (DNS) server, which dispatches the user requests among the servers through the URL name to the IP address mapping mechanism, is integrated with a redirection request mechanism based on HTTP. This should alleviate the side-effect of caching the IP address mapping at intermediate name servers. We compare many alternative mechanisms, including synchronous vs. asynchronous activation and centralized vs. distributed decisions on redirection. Moreover, we analyze the reassignment of entire domains or individual client requests, different types of status information and different server selection policies for redirecting requests. Our results show that the combination of centralized and distributed dispatching policies allows the Web server cluster to handle high load skews in the WWW environment. Geo-replicated services need an effective way to direct client requests to a particular location, based on performance, load, and cost. This paper presents DONAR, a distributed system that can offload the burden of replica selection, while providing these services with a sufficiently expressive interface for specifying mapping policies. Most existing approaches for replica selection rely on either central coordination (which has reliability, security, and scalability limitations) or distributed heuristics (which lead to suboptimal request distributions, or even instability). In contrast, the distributed mapping nodes in DONAR run a simple, efficient algorithm to coordinate their replica-selection decisions for clients. The protocol solves an optimization problem that jointly considers both client performance and server load, allowing us to show that the distributed algorithm is stable and effective. Experiments with our DONAR prototype--providing replica selection for CoralCDN and the Measurement Lab--demonstrate that our algorithm performs well "in the wild." Our prototype supports DNS- and HTTP-based redirection, IP anycast, and a secure update protocol, and can handle many customer services with diverse policy objectives.