Efficient cache invalidation schemes for mobile data accesses

This paper presents two cache invalidation schemes to maintain data consistency between the server and clients in a mobile environment. Designed according to real situations like MANET, the Adaptive Data Dividing (ADD) scheme divides data into groups of different utilization ratios and varies group broadcast intervals to reduce data access time and bandwidth consumption. The Data Validity Defining (DVD) scheme aims to solve the validity problem of cached data items, which usually happens after clients disconnect from the server. Experimental evaluations and performance analyses exhibit that the two schemes outperform most existing cache invalidation schemes in terms of data access time, cache miss ratios, query uplink ratios and bandwidth consumption.     

A cache invalidation strategy for mobile networks

The diversity of services delivered over wireless channels has increased people's desire in ubiquitously accessing these services from their mobile devices. However, a ubiquitous mobile computing environment faces several challenges such as scarce bandwidth, limited energy resources, and frequent disconnection of the server and mobile devices. Caching frequently accessed data is an effective technique to improve the network performance because it reduces the network congestion, the query delay, and the power consumption. When caching is used, maintaining cache consistency becomes a major challenge since data items that are updated on the server should be also updated in the cache of the mobile devices. In this paper we propose a new cache invalidation scheme called Selective Adaptive Sorted (SAS) cache invalidation strategy that overcomes the false invalidation problem that exists in most of the invalidation strategies found in the literature. The performance of the proposed strategy is evaluated and compared with the selective cache invalidation strategy and the updated invalidation report startegy found in the literature. Results showed that a significant cost reduction can be obtained with the proposed strategy when measuring performance metrics such as delay, bandwidth, and energy.     

A scalable low-latency cache invalidation strategy for mobile environments

Caching frequently accessed data items on the client side is an effective technique for improving performance in a mobile environment. Classical cache invalidation strategies are not suitable for mobile environments due to frequent disconnections and mobility of the clients. One attractive cache invalidation technique is based on invalidation reports (IRs). However, the IR-based cache invalidation solution has two major drawbacks, which have not been addressed in previous research. First, there is a long query latency associated with this solution since a client cannot answer the query until the next IR interval. Second, when the server updates a hot data item, all clients have to query the server and get the data from the server separately, which wastes a large amount of bandwidth. In this paper, we propose an IR-based cache invalidation algorithm, which can significantly reduce the query latency and efficiently utilize the broadcast bandwidth. Detailed analytical analysis and simulation experiments are carried out to evaluate the proposed methodology. Compared to previous IR-based schemes, our scheme can significantly improve the throughput and reduce the query latency, the number of uplink request, and the broadcast bandwidth requirements.     

Performance analysis of location-dependent cache invalidation schemes for mobile environments

Mobile location-dependent information services are gaining increasing interest in both academic and industrial communities. In these services, data values depend on their locations. Caching frequently accessed data on mobile clients can help save wireless bandwidth and improve system performance. However, since client location changes constantly, location-dependent data may become obsolete not only due to updates performed on data items but also because of client movements across the network. To the best of the authors' knowledge, previous work on cache invalidation issues focused on data updates only. This paper considers data inconsistency caused by client movements and proposes three location-dependent cache invalidation schemes. The performance for the proposed schemes is investigated by both analytical study and simulation experiments in a scenario where temporal- and location-dependent updates coexist. Both analytical and experimental results show that, in most cases, the proposed methods substantially outperform the NSI scheme, which drops the entire cache contents when hand-off is performed.     

A cache invalidation scheme for continuous partial match queries in mobile computing environments

The continuous partial match query is a partial match query whose result remains consistently in the client’s memory. Conventional cache invalidation methods for mobile clients are record ID-based. However, since the partial match query uses content-based retrieval, the conventional ID-based approaches cannot efficiently manage the cache consistency of mobile clients. In this paper, we propose a predicate-based cache invalidation scheme for continuous partial match queries in mobile computing environments. We represent the cache state of a mobile client as a predicate, and also construct a cache invalidation report (CIR), which the server broadcasts to clients for cache management, with predicates. In order to reduce the amount of information that is needed for cache management, we propose a set of methods for CIR construction (in the server) and identification of invalidated data (in the client). Through experiments, we show that the predicate-based approach is very effective for the cache management of mobile clients.     

Adaptive per-user per-object cache consistency management for mobile data access in wireless mesh networks

We propose and analyze an adaptive per-user per-object cache consistency management (APPCCM) scheme for mobile data access in wireless mesh networks. APPCCM supports strong data consistency semantics through integrated cache consistency and mobility management. The objective of APPCCM is to minimize the overall network cost incurred due to data query/update processing, cache consistency management, and mobility management. In APPCCM, data objects can be adaptively cached at the mesh clients directly or at mesh routers dynamically selected by APPCCM. APPCCM is adaptive, per-user and per-object as the decision regarding where to cache a data object accessed by a mesh client is made dynamically, depending on the mesh client’s mobility and data query/update characteristics, and the network’s conditions. We develop analytical models for evaluating the performance of APPCCM and devise a computational procedure for dynamically calculating the overall network cost incurred. We demonstrate via both model-based analysis and simulation validation that APPCCM outperforms non-adaptive cache consistency management schemes that always cache data objects at the mesh client, or at the mesh client’s current serving mesh router for mobile data access in wireless mesh networks.     

Broadcast-based group invalidation: An energy-efficient cache invalidation strategy

In a wireless environment, mobile clients may cache frequently accessed data to reduce the contention on the narrow bandwidth of the wireless channel. However, to minimize energy consumption, mobile clients may also often operate in a disconnected mode. As a result, the clients may miss some cache invalidation reports broadcast by a server. Thus, upon reconnection, a cache invalidation scheme must be employed to ensure the validity of the cached data. Existing techniques either require the clients to discard the cached data entirely, or require the clients to transmit uplink messages to a server. While the former eliminates the benefits of caching, the latter may lead to high energy consumption, poor channel utilization, and costs. In this paper, we present a new cache invalidation scheme, called Broadcast-Based Group Invalidation (BGI), that retains the benefits of caching while avoiding unnecessary transmissions (which translates to energy saving, better channel utilization, and lower costs). Under BGI, a pair of invalidation reports is broadcast periodically. While the object invalidation report enables the clients to salvage as many recently cached objects as possible, the group invalidation report cuts down on false invalidation. We conduct extensive studies based on a simulation model. The simulation results show that BGI consumes less energy and is superior over existing techniques.     

Scalable access to scientific data

The author use a simple analytic model to analyze the scalability of an infrastructure that generates high-level data products derived from raw data and then delivers them in response to user requests. He also discusses the concept of metadata and how it generally facilitates access to scientific data.     

面向移动端基于社交关系的图片缓存替换算法

随着移动终端深入人们的生活,移动社交APP得到了广泛使用。在移动社交APP中往往会使用大量的图片资源,如微信朋友圈、Instagram的图片分享等。在APP中浏览图片会消耗较多的网络流量,影响加载速度,因此大部分APP采用首先显示缩略图,根据用户需求再加载原图的策略。在服务器端也采用缓存技术来加快缩略图产生时间,减少磁盘I/O。但是,当前的缓存机制更多关注的是缓存的访问频率、最近访问时间等因素,并没有过多关注数据生成用户之间的社交关系,也没有考虑移动用户对缩略图和原图的不同访问模式。把缓存划分为两个部分:缩略图缓存区和原图缓存区,提出了基于社交关系的图片缓存替换算法,在传统缓存替换算法的基础上增加用户的社交关系以及缩略图和原图的关联关系,通过计算图片的缓存价值进行缓存替换。实验表明,所提出的基于社交关系的图片缓存替换算法对于缩略图和原图的缓存命中率都有明显提高。     

An update-based step-wise optimal cache replacement for wireless data access

Many network applications requires access to most up-to-date information. An update event makes the corresponding cached data item obsolete, and cache hits due to obsolete data items become simply useless to those applications. Frequently accessed but infrequently updated data items should get higher preference while caching, and infrequently accessed but frequently updated items should have lower preference. Such items may not be cached at all or should be evicted from the cache to accommodate items with higher preference. In wireless networks, remote data access is typically more expensive than in wired networks. Hence, an efficient caching scheme considers both data access and update patterns can better reduce data transmissions in wireless networks. In this paper, we propose a step-wise optimal update-based replacement policy, called the Update-based Step-wise Optimal (USO) policy, for wireless data networks to optimize transmission cost by increasing effective hit ratio. Our cache replacement policy is based on the idea of giving preference to frequently accessed but infrequently updated data, and is supported by an analytical model with quantitative analysis. We also present results from our extensive simulations. We demonstrate that (1) the analytical model is validated by the simulation results and (2) the proposed scheme outperforms the Least Frequently Used (LFU) scheme in terms of effective hit ratio and communication cost.     

Scalable cache consistency for hierarchically structured multiprocessors

This paper presents a new cache consistency scheme for hierarchically structured shared-memory multiprocessors. The scheme is simple, fast and efficient, and it does not require a large amount of state information to be maintained. The scheme exploits the broadcast capability of these systems, but limits the extent of the broadcasts by means of a novel filtering mechanism. As a specific example, it is shown how the proposed cache consistency scheme can be implemented on the Hector multiprocessor architecture. Using trace-driven simulations, we demonstrate that the scheme is scalable and performs well for common applications.     

Scalable algorithms for estimating flow length distributions from sampled data

With the rapid growth of link speed, obtaining detailed traffic statistics becomes much more difficult. In order to reduce the resource consumption of measurement systems, more and more passive traffic measurement employs sampling at the packet level. Packet sampling has become an attractive and scalable method to measure flow data on high-speed links. However, knowing the length distributions of traffic flows passing through a network link is very useful for network operation and management. In this paper, we consider the problem of estimating flow length distributions based on sampled flow data. This paper introduces two algorithms for estimating flow length distributions, fitting estimation and factoring estimation. The fitting estimation uses piecewise Pareto distribution to fit the original traffic for a small sampling period. The factoring estimation is used for a large sampling period. It first factorizes the large sampling period into a product of some smaller integer factors, then iteratively invokes fitting estimation or other algorithms such as ${\textit{EM}}$ in the arranged order of the factors. Evaluations of the proposed algorithms on large Internet traces obtained from several sources demonstrate that they have high measurement accuracy with low computation overhead. The algorithms allow us to recover the complete flow length distributions.     

An evaluation of cache invalidation strategies in wirelessenvironments

Caching can reduce the bandwidth requirement in a wireless computing environment as well as minimize the energy consumption of wireless portable computers. To facilitate mobile clients in ascertaining the validity of their cache content, servers periodically broadcast cache invalidation reports that contain information of data that has been updated. However, as mobile clients may operate in a doze or even totally disconnected mode (to conserve energy), it is possible that some reports may be missed and the clients are forced to discard the entire cache content. In this paper, we reexamine the issue of designing cache invalidation strategies. We identify the basic issues in designing cache invalidation strategies. From the solutions to these issues, a large set of cache invalidation schemes can be constructed. We evaluate the performance of four representative algorithms-two of which are known algorithms (i.e., Dual-Report Cache Invalidation and Bit-Sequences) while the other two are their counterparts that exploit selective tuning (namely, Selective Dual-Report Cache Invalidation and Bit-Sequences with Bit Count). Our study shows that the two proposed schemes are not only effective in salvaging the cache content but consume significantly less energy than their counterparts. While the Selective Dual-Report Cache Invalidation scheme performs best in most cases, it is inferior to the Bit-Sequences with the Bit-Count scheme under high update rates     

Scalable algorithms for association mining

Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. We present efficient algorithms for the discovery of frequent itemsets which forms the compute intensive phase of the task. The algorithms utilize the structural properties of frequent itemsets to facilitate fast discovery. The items are organized into a subset lattice search space, which is decomposed into small independent chunks or sublattices, which can be solved in memory. Efficient lattice traversal techniques are presented which quickly identify all the long frequent itemsets and their subsets if required. We also present the effect of using different database layout schemes combined with the proposed decomposition and traversal techniques. We experimentally compare the new algorithms against the previous approaches, obtaining improvements of more than an order of magnitude for our test databases     

Benefit based cache data placement and update for mobile peer to peer networks

Mobile Peer to Peer (MP2P) networks provide decentralization, self-organization, scalability characters, but suffer from high latency and link break problems. In this paper, we study the cache/replication placement and cache update problems arising in such kind of networks. While researchers have proposed various replication placement algorithms to place data across the network to address the problem, it was proven as NP-hard. As a result, many heuristic algorithms have been brought forward for solving the problem. In this article, we propose an effective and low cost cache placement strategy combined with an update scheme which can be easily implemented in a decentralized way. The contribution of this paper is the adaptive and flexible cache placement and update algorithms designed for real MP2P network usage. The combination of MP2P cache placement and update is the novelty of this article. Extensive experiments are conducted to demonstrate the efficiency of the cache placement and update scheme.     

Optimizing graph algorithms for improved cache performance

We develop algorithmic optimizations to improve the cache performance of four fundamental graph algorithms. We present a cache-oblivious implementation of the Floyd-Warshall algorithm for the fundamental graph problem of all-pairs shortest paths by relaxing some dependencies in the iterative version. We show that this implementation achieves the lower bound on processor-memory traffic of /spl Omega/(N/sup 3///spl radic/C), where N and C are the problem size and cache size, respectively. Experimental results show that this cache-oblivious implementation shows more than six times the improvement in real execution time over that of the iterative implementation with the usual row major data layout, on three state-of-the-art architectures. Second, we address Dijkstra's algorithm for the single-source shortest paths problem and Prim's algorithm for minimum spanning tree problem. For these algorithms, we demonstrate up to two times the improvement in real execution time by using a simple cache-friendly graph representation, namely adjacency arrays. Finally, we address the matching algorithm for bipartite graphs. We show performance improvements of two to three times in real execution time by using the technique of making the algorithm initially work on subproblems to generate a suboptimal solution and, then, solving the whole problem using the suboptimal solution as a starting point. Experimental results are shown for the Pentium III, UltraSPARC III, Alpha 21264, and MIPS R12000 machines.     

Massively parallel algorithms for trace-driven cache simulations

Considers the use of massively parallel architectures to execute a trace-driven simulation of a single cache set. A method is presented for the least-recently-used (LRU) policy, which, regardless of the set size C, runs in time O(log N) using N processors on the EREW (exclusive read, exclusive write) parallel model. A simpler LRU simulation algorithm is given that runs in O(C log N) time using N/log N processors. We present timings of this algorithm's implementation on the MasPar MP-1, a machine with 16384 processors. A broad class of reference-based line replacement policies are considered, which includes LRU as well as the least-frequently-used (LFU) and random replacement policies. A simulation method is presented for any such policy that, on any trace of length N directed to a C line set, runs in O(C log N) time with high probability using N processors on the EREW model. The algorithms are simple, have very little space overhead, and are well suited for SIMD implementation     

基于最小效用的流媒体缓存替换算法

提出最小缓存替换算法SCU-K，综合考虑流媒体文件最近K次访问情况，使缓存大小动态适应媒体流行度、字节有用性和已缓存部分大小的变化，降低了文件前缀部分被替换的概率，避免LRU和LFU算法中出现的媒体文件被连续替换的问题。在与LRU，LFU和LRU-2算法的对比实验中，SCU-K算法在提高缓存空间利用率、字节命中率和降低启动延迟方面具有更好的性能。     

SCALAR: Scalable data lookup and replication protocol for mobile ad hoc networks

Data replication, as an essential service for MANETs, is used to increase data availability by creating local or nearly located copies of frequently used items, reduce communication overhead, achieve fault-tolerance and load balancing. Data replication protocols proposed for MANETs are often prone to scalability problems due to their definitions or underlying routing protocols they are based on. In particular, they exhibit poor performance when the network size is scaled up. However, scalability is an important criterion for several MANET applications. We propose a scalable and reactive data replication approach, named SCALAR, combined with a low-cost data lookup protocol. SCALAR is a virtual backbone based solution, in which the network nodes construct a connected dominating set based on network topology graph. To the best of our knowledge, SCALAR is the first work applying virtual backbone structure to operate a data lookup and replication process in MANETs. Theoretical message-complexity analysis of the proposed protocols is given. Extensive simulations are performed to analyze and compare the behavior of SCALAR, and it is shown to outperform the other solutions in terms of data accessibility, message overhead and query deepness. It is also demonstrated as an efficient solution for high-density, high-load, large-scale mobile ad hoc networks.