A Lightweight and Cooperative Multifactor Considered File Replication Method in Structured P2P Systems

File replication and file consistency maintenance are two important protocols for achieving overall high performance of peer-to-peer file sharing systems. In spite of the significant dependency of consistency maintenance on file replication, there has been little file replication research devoted to tackling the dependency issue. Most traditional file replication protocols focus on improving file lookup efficiency without considering the subsequent consistency maintenance. This paper presents a COoperative file Replication Protocol (CORP). CORP observes a set of factors including file update rate, file popularity, node available capacity, file load and node locality that affect the efficiency of consistency maintenance. It considers these factors to achieve high efficiency not only in file replication but also in consistency maintenance. CORP generates less replicas and optimally chooses infrequently-updated or popular files to replicate. In addition, it makes file replicas in physically close nodes. Further, CORP can dynamically adjust the number of replicas based on ever-changing file popularity and visit pattern. Simulation results demonstrate the efficiency and effectiveness of CORP in comparison with other file replication protocols. It dramatically reduces the overhead of both file replication and consistency maintenance. Moreover, it yields significant improvement in reducing overloaded nodes.

Popular files could exhaust the capacity of the file owner node, leading to low efficiency in P2P file sharing systems. File replication is an effective method to deal with this problem by distributing load over replica nodes. Recently, numerous file replication methods have been proposed for P2P content delivery networks on the Internet. However, due to mobility and resource constraints in the wireless networks, these replication techniques designed for wired networks may not be applicable to the wireless networks. Aiming at the issue of file replication, an adaptive file replication scheme is proposed for wireless mesh networks in this paper. Based on file popularity and node’s utilization, the optimal number of replicas needed for each file is determined automatically by the responsible node in a distributed way. By using multiple-adjacency codes based on hypercube, a perfect placement scheme is achieved for each file replica, thus, it reduces access hops between the file requester node and some nearby nodes, which can provide the requesting file. Furthermore, a solution is adopted, which autonomously decides whether to replicate file, and adaptively adjusts the file replica nodes based on time-varying file popularity and node’s load in the P2P systems having dynamic characteristics. Simulation results demonstrate that our proposed algorithm performs much better than similar ones, and yield significant improvement on the effectiveness in terms of both file access cost and overloaded nodes reduction.

A Dynamic Fault Tolerant Threshold based Replication Mechanism in Distributed Environment

An effort has been made to propose an adaptive, trust based, on demand and reliable file replication approach for distributed environment. The work proposes an active replication mechanism for file replication; file access and performance transparency to system, thereby ensuring replication decisions such as when to replicate, where to replicate, load status of the node selected for replication and avoidance of redundant replica on that node. The proposed model introduces File Replication Server (FRS) that replicates the file, when total number of request for it reaches the threshold value, adhering to replication decision. If all replicas of file are not synchronized with each other, this drives system into inconsistent state. To keep files consistent, changes made at one replica of file should be reflected on other replicas in minimum possible time. Unlike conventional approaches viz., Write Update and Write Invalidate, in which either all or any fixed master replica is updated respectively, the proposed approach transfers the role of master replica to the last modified replica. File replica is updated on-demand by only propagating the required partial updates. The master replica immediately computes the file content modifications but propagates them only on-demand. Once a node gets itself registered, it becomes the part of elite FRS community. This paper introduces basic trust parameters and adaptive factors in computing trustworthiness of peer FRS, namely, frequency of the request for a particular file that a FRS perform, registration type of node i.e., paid or unpaid, write operation not permitted if trust value of a FRS is less than threshold, feedback that a FRS gives about other FRS and authenticity of the session key. Simulation results show that during high file request scenario for a particular file, frequently accessed files are replicated on other FRSs dynamically and file request is redirected in transparent manner, thus reducing request completion time by about 28.78–47.24 % as compared to FTP. Experimental results shows that various factors viz., file size, size of modifications and number of replicas to be updated affects the time to propagate the changes to other replicas. Percentage reduction in time for propagating these changes varies from 31.56 to 78.1 %. Similarly, the reduction in time for updating replicas simultaneously varies from 78.17 to 85.37 %. Though the percentage increase in time required for acquiring the keys to access the services with trust based security model varies from 11.94 to 17.49 %, the same is compensated by reduction in time for updating replicas. In order to ascertain stability of proposed model, Calculus of Communicating System (CCS) for proposed model is compiled on CWB-NC tool and bisimulation equivalence is proved for proposed file replication model.

Data replication is a common method to reduce the bandwidth consumption and the access latency in distributed systems. The existing replication methods mostly deal with the read-only data, thus the replica management mechanism is relatively simple. Most replication methods replicate files in all nodes or two endpoints on a query path. Naturally, the larger number of replicas, the better performance it can obtain. However, these methods lead to high overhead for unnecessary file replications and consistency maintenance. This paper presents a dynamic minimum access cost based replication strategy (MAC replication strategy). MAC replication strategy takes into account the access frequency, the status of the network connection and average response time to perform optimal replication. It first selects the popular files. To each popular file, the average response time is calculated to determine which logical resource should be replicated. Then MAC replication strategy calculates an appropriate site to replicate for better shortening the response time of the data resource. Simulation results demonstrate the efficiency and effectiveness of MAC replication strategy in comparison with other approaches.

Replication is one of the key techniques used in distributed systems to improve high data availability, data access performance and data reliability. To optimize the maximum benefits from file replication, a systems that includes replicas need a strategy for selecting and accessing suitable replicas. A replica selection strategy determines the available replicas and chooses the most access files. In most of these access frequency based solutions or popularity of files are assuming that files are independent of each other. In contrast, distributed systems such as peer-to-peer file sharing, and mobile database, files may be dependent or correlated to one another. Thus, this paper focused on the combination of popularity and affinity files as the most important parameters in selecting replicas in distributed environments. Herein, a replica selection is proposed focusing on popular files and affinity files. The idea is to improve data availability in distributed data replica selection strategy. A P2P simulator, PeerSim, is used to evaluate the performance of the dynamic replica selection strategy. The simulation results provided a proof that the proposed affinity replica selection has contributed towards a new dimension of replica selection strategy that incorporates the affinity and popularity of file replicas in distributed systems.

Random walks is an excellent search mechanism in unstructured P2P network. However, it generates long delay and makes some resources indiscoverable, especially for uncommon files. File replication strategy can improve the performance of random walks. But it has high overhead. An efficient replication strategy LQPD is presented. In LQPD, file replication operation is triggered only when the length of query path exceeds user-acceptable delay. Experimental results show LQPD can get better performance than other strategies with the same number of file replicas in a Gnutella-like overlay network.

Replication technology is commonly used to improve data availability and reduce data access latency in the cloud storage system by providing users with different replicas of the same service. Most current approaches largely focus on system performance improvement, neglecting management cost in deciding replicas number and their store places, which cause great financial burden for cloud users because the cost for replicas storage and consistency maintenance may lead to high overhead with the number of new replicas increased in a pay-as-you-go paradigm. In this paper, towards achieving the approximate minimum data sets management cost benchmark in a practical manner, we propose a replicas placements strategy from cost-effective view with the premise that system performance meets requirements. Firstly, we design data sets management cost models, including storage cost and transfer cost. Secondly, we use the access frequency and the average response time to decide which data set should be replicated. Then, the method of calculating replicas’ number and their store places with minimum management cost is proposed based on location problem graph. Both the theoretical analysis and simulations have shown that the proposed strategy offers the benefits of lower management cost with fewer replicas.

Caching frequently accessed data objects at the local buffer of a mobile user (MU) has been found to be very effective in improving information availability in mobile wireless environments. Several mechanisms have been proposed in the literature to address the challenging problem of cache consistency in cellular wireless networks. However, these mechanisms are limited to single cell systems. In this paper, we develop a novel Dynamic Scalable Asynchronous Cache Consistency Scheme (DSACCS) that can adaptively maintain mobile data objects globally or locally depending on the minimum consistency maintenance cost in multi-cell systems. The cost function is derived by taking into account each data object's update frequency, MUs' access pattern and roaming frequency, number of cells and number of MUs in the system. Extensive simulation studies demonstrate that DSACCS outperforms three existing cache strategies extended to multi-cell environments. The three cache consistency strategies are homogeneous invalidation reports (IRs), inhomogeneous IR without roaming check, and inhomogeneous IR with roaming check. Finally, an improvisation of DSACCS, called DSACCS-G, is proposed for grouping cells in order to facilitate effective cache consistency maintenance in multi-cell systems.

The decentralized peer-to-peer (P2P) file sharing systems organize nodes into structured or unstructured networks. The advantages of the unstructured P2P systems are that they have lower maintenance overhead and can better adapt to node heterogeneity as well as network dynamics. However, the search process in unstructured systems is not as efficient as in structured P2P systems because the same search message may go through a node multiple times. To facilitate the complex search and improve the search efficiency, we propose a novel approach of assigning identifications to nodes in an unstructured system. Our method can prevent a node from receiving duplicate search messages and retain the low maintenance overhead for the system. The performance evaluations demonstrate that the proposed approach can improve the search efficiency of unstructured P2P systems while keeping the maintenance overhead at a comparable or even lower level, compared with the traditional unstructured systems.

Trading quantization precision for update rates for systems with limited communication in the uplink channel

Accuracy and tracking update rates play a vital role in determining the quality of Augmented Reality(AR) and Virtual Reality(VR) applications. Applications like soldier training, gaming, simulations & virtual conferencing need a high accuracy tracking with update frequency above 20Hz for an immersible experience of reality. Current research techniques combine more than one sensor like camera, infrared, magnetometers and Inertial Measurement Units (IMU) to achieve this goal. In this paper, we develop and validate a novel algorithm for accurate positioning and tracking using inertial and vision-based sensing techniques. The inertial sensing utilizes accelerometers and gyroscopes to measure rates and accelerations in the body fixed frame and computes orientations and positions via integration. The vision-based sensing uses camera and image processing techniques to compute the position and orientation. The sensor fusion algorithm proposed in this work uses the complementary characteristics of these two independent systems to compute an accurate tracking solution and minimizes the error due to sensor noise, drift and different update rates of camera and IMU. The algorithm is computationally efficient, implemented on a low cost hardware and is capable of an update rate up to 100 Hz. The position and orientation accuracy of the sensor fusion is within 6mm & 1.5°. By using the fuzzy rule sets and adaptive filtering of data, we reduce the computational requirement less than the conventional methods (such as Kalman filtering). We have compared the accuracy of this sensor fusion algorithm with a commercial infrared tracking system. It can be noted that outcome accuracy of this COTS IMU and camera sensor fusion approach is as good as the commercial tracking system at a fraction of the cost.

This paper derives the optimal search time and the optimal search cost that can be achieved in unstructured peer-to-peer networks when the demand pattern exhibits clustering (i.e. file popularities vary across the set of nodes in the network). Clustering in file popularity patterns is evident from measurements on deployed peer-to-peer file sharing networks. In this paper, we provide mechanisms for modeling clustering in file popularity distributions and the consequent non-uniform distribution of file replicas. We derive relations that show the effect of the number of replicas of a file on the search time and on the search cost for a search for that file for the clustered demands case in such networks for both random walk and flooding search mechanisms. The derived relations are used to obtain the optimal search performance for the case of flooding search mechanisms. The potential performance benefit that clustering in demand patterns affords is captured by our results. Interestingly, the performance gains are shown to be independent of whether the search network topology reflects the clustering in file popularity (the optimal file replica distribution to obtain these performance gains, however, does depend on the search network topology).

The publication of the pivotal state machine replication protocol PBFT laid the foundation for a body of BFT protocols. We introduce a probabilistic model for evaluating BFT protocols in the presence of dynamic link and crash failures. The model is derived from the communication pattern, facilitating an adaptation to other protocols. The state of replicas is captured and used to derive the success probability of the protocol execution. To this end, we examine the influence of link and crash failure rates as well as the number of replicas. A comparison in protocol behavior of PBFT, Zyzzyva and SBFT is performed.

Most replication methods either monitor the popularity of files or use complicated functions to calculate the overall cost of whether or not a replication decision or a deletion decision should be issued. However, once the replication decision is issued, the popularity of the files is changed and may have already impacted access latency and resource usage. This article proposes a decision-tree-based predictive file replication strategy that forecasts files’ future popularity based on their characteristics on the Grids. The proposed strategy has shown superb performance in terms of mean job time and effective network usage compared with the other two replication strategies, LRU and Economic under OptorSim simulation environment.