Cooperative Caching Scheme Research Articles

Improving on-demand data access efficiency in MANETs with cooperative caching

Mobile ad hoc networks (MANETs) provide an attractive solution for networking in the situations where network infrastructure or service subscription is not available. Its usage can further be extended by enabling communications with external networks such as the Internet or cellular networks through gateways. However, data access applications in MANETs suffer from dynamic network connections and restricted resources. While most of the research focuses on media (or medium) access control (MAC) and routing layer solutions, we explore the possibility of making use of data locality and the commonality in users’ interests at the application level. In this paper, we investigate how cooperative caching can be used to improve data access efficiency in MANETs. We propose COOP, a novel cooperative caching scheme for on-demand data access applications in MANETs. The objective is to improve data availability and access efficiency by collaborating local resources of mobile nodes. COOP addresses two basic problems of cooperative caching: cache resolution and cache management. To improve data availability and access efficiency, COOP discovers data sources which induce less communication overhead by utilizing cooperation zones, historical profiles, and hop-by-hop resolution. For cache management, COOP increases the effective capacity of cooperative caches by minimizing caching duplications within the cooperation zone and accommodating more data varieties. The performance of COOP is studied using mathematical analysis and simulations from the perspectives of data availability, time efficiency, and energy efficiency. The analysis and simulation results show that COOP significantly reduces response delay and improves data availability with proper settings of the cooperation zone radius.

Exploiting caching in heterogeneous mobile environment

AbstractSparse connectivity, limited energy, and restricted memory of Mobile Hosts (MHs) are the main characteristics of today's Mobile Ad hoc NETwork (MANET). Present wireless technology is now enabling MHs not only to have multi‐hop communication among themselves, but also to have direct connection with an Access Point (AP) also. The emergence of such heterogeneous technologies brings cooperative caching to reality wherein MHs can access data items from caches at MHs in their neighborhood and can drastically minimize query latency. This key technique reduces the number of uplink channel requests, alleviates server load, and increases data availability. In this paper, we assume a heterogonous mobile environment where combination of ad hoc communication and infrastructured APs can be used to better manage the data needs of MHs through cooperative caching. We call such an environment as Cooperation‐based Access Point MANET (CAPMANET). We present a Hop‐Oriented Cooperative Caching (HOCC) scheme for CAPMANET which helps in reducing the communication overhead and the query latency. HOCC employs a hybrid Pull with Push (PwP) mechanism to maintain data consistency. Simulation results demonstrate that HOCC outperforms the pure push and pure pull‐based strategies by taking advantages of underlying characteristics and avoiding associated weaknesses. Copyright © 2007 John Wiley & Sons, Ltd.

GroCoca: group-based peer-to-peer cooperative caching in mobile environment

In a mobile cooperative caching environment, we observe the need for cooperating peers to cache useful data items together, so as to improve cache hit from peers. This could be achieved by capturing the data requirement of individual peers in conjunction with their mobility pattern, for which we realized via a GROup-based COoperative CAching scheme (GroCoca). In GroCoca, we define a tightly-coupled group (TCG) as a collection of peers that possess similar mobility pattern and display similar data affinity. A family of algorithms is proposed to discover and maintain all TCGs dynamically. Furthermore, two cooperative cache management protocols, namely, cooperative cache admission control and replacement, are designed to control data replicas and improve data accessibility in TCGs. A cache signature scheme is also adopted in GroCoca in order to provide information for the mobile clients to determine whether their TCG members are likely caching their desired data items and to perform cooperative cache replacement Experimental results show that GroCoca outperforms the conventional caching scheme and standard COoperative CAching scheme (COCA) in terms of access latency and global cache hit ratio. However, GroCoca generally incurs higher power consumption.

Supporting mobile device communications in the presence of broadcast servers

Broadcast data dissemination is well-suited for mobile wireless environments, where bandwidth is scarce and mutual interference must be minimised. However, broadcasting monopolises the medium, precluding clients from performing any other communication. We address this problem in two ways. Firstly, we segment the server broadcast, with intervening periods of silence, during which the wireless devices may communicate. Secondly, we reduce the average access delay for clients using a novel cooperative caching scheme. Our scheme is fully decentralised and uses information available locally at the client. Our results show that our model prevents the server from monopolising the medium and that our caching strategy reduces client access delays significantly.

Cooperative Caching Strategy in Mobile Ad Hoc Networks Based on Clusters

In this paper, we present a scheme, called Cluster Cooperative (CC) for caching in mobile ad hoc networks. In CC scheme, the network topology is partitioned into non-overlapping clusters based on the physical network proximity. For a local cache miss, each client looks for data item in the cluster. If no client inside the cluster has cached the requested item, the request is forwarded to the next client on the routing path towards server. A cache replacement policy, called Least Utility Value with Migration (LUV-Mi) is developed. The LUV-Mi policy is suitable for cooperation in clustered ad hoc environment because it considers the performance of an entire cluster along with the performance of local client. Simulation experiments show that CC caching mechanism achieves significant improvements in cache hit ratio and average query latency in comparison with other caching strategies.

Cooperative Caching for Chip Multiprocessors

This paper presents CMP Cooperative Caching, a unified framework to manage a CMP's aggregate on-chip cache resources. Cooperative caching combines the strengths of private and shared cache organizations by forming an aggregate "shared" cache through cooperation among private caches. Locally active data are attracted to the private caches by their accessing processors to reduce remote on-chip references, while globally active data are cooperatively identified and kept in the aggregate cache to reduce off-chip accesses. Examples of cooperation include cache-to-cache transfers of clean data, replication-aware data replacement, and global replacement of inactive data. These policies can be implemented by modifying an existing cache replacement policy and cache coherence protocol, or by the new implementation of a directory-based protocol presented in this paper. Our evaluation using full-system simulation shows that cooperative caching achieves an off-chip miss rate similar to that of a shared cache, and a local cache hit rate similar to that of using private caches. Cooperative caching performs robustly over a range of system/cache sizes and memory latencies. For an 8-core CMP with 1MB L2 cache per core, the best cooperative caching scheme improves the performance of multithreaded commercial workloads by 5-11% compared with a shared cache and 4-38% compared with private caches. For a 4-core CMP running multiprogrammed SPEC2000 workloads, cooperative caching is on average 11% and 6% faster than shared and private cache organizations, respectively.

Weblins: A scalable WWW cluster-based server

With the ever-growing web traffic, cluster-based web servers have become very important to the Internet infrastructure. Thus, making the best use of all available resources in the cluster to achieve high performance is a significant research issue. In this paper, we present Weblins, a cluster-based web server that can achieve good throughput. Weblins has Gobelins operating system as platform. Gobelins is an efficient single system image operating system that transparently makes use of the resources available in the cluster. The architecture of Weblins is fully distributed. Weblins implements a content-aware request distribution policy via a new interface on top of Gobelins. Popular web files are dynamically replicated on all nodes via a cooperative caching mechanism. For the non-popular files, the requests are handed-off to the corresponding nodes via the TCP Handoff protocol. Simulation results show that the strategy used by Weblins is more suitable for cluster-based Web severs in comparison with pure content-aware strategy and pure cooperative caching strategy.

Content-aware cooperative caching for cluster-based web servers

Most traditional cooperative caching schemes were developed for network file systems but were not designed for cluster-based web servers with content-based request distribution. Hence, although the schemes are applied to the web servers, their performance is not good due to high disk accesses and large block access latency. This paper proposes and evaluates a new cooperative caching scheme suitable to file systems in web servers. It uses a cache replacement policy, called duplicate first copy replacement, to avoid caching unnecessary data produced during serving requests and to minimize disk accesses. In addition it reduces block access latency required to fetch a file-block in the cooperative cache. A simulation shows that our cooperating caching decreases the disk access ratio by 29%, and reduces block access latency by about 26% when compared to the existing cooperative algorithms.