Dynamic resource allocation strategy for latency-critical and computation-intensive applications in cloud–edge environment

This paper introduces a new approach to database disk buffering, called the LFU-K method. The LFU-K page replacement algorithm is an improvement to the Least Frequently Used (LFU) algorithm. The paper proposes a theoretical-probability model for formal description of LFU-K algorithm. Using this model we evaluate estimations for the LFU-K parameters. This paper also describes an implementation of LFU-2 policy. As we demonstrate by trace-driven simulation experiments, the LFU-2 algorithm provides significant improvement over conventional buffering algorithms for the shared-nothing database systems.

LFU-K: An effective buffer management replacement algorithm

This paper mainly studies the vulnerability intelligent early warning technology in the IoT environment, and studies the network security assessment method based on the attack graph association analysis of the IoT environment, and analyzes the attack graph generation algorithm. Firstly, it uses the attack graph technology to establish a network security evaluation model based on the vulnerability association analysis in the IoT environment. The attack graph generation algorithm is improved. The key attack path of the attack graph in the IoT environment is searched according to the node weight value. The key attack path of the network attack graph is used to measure the whole network security, and the security under the IoT environment is given. The measurement calculation model is used to realize the quantitative analysis of the security status of the IoT environment by using the attack graph. Secondly, an intelligent early warning vulnerability detection algorithm based on the dynamic stain propagation model in the IoT environment is proposed, focusing on the introduction of stains and the inspection of stains. A static detection method for early warning vulnerabilities based on the counter-example of the IoT is proposed. Through the flow detection and context sensitive detection, a possible buffer early warning vulnerability is discovered. The driver crawler realizes automatic detection, and uses function hijacking to detect the execution of the stain data. In the experimental environment, compared with the existing tools, the experimental data shows that the algorithm improves the accuracy, recall rate and efficiency of the unfiltered vulnerability of intelligent early warning detection, and proves that the proposed algorithm can effectively detect the vulnerability.

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An Intelligent Communication Warning Vulnerability Detection Algorithm Based on IoT Technology

A quite significant issue with the current location-based services application is to securely store information for users on the network in order to quickly access the data items. One way to do this is to store data items that have a high likelihood of subsequent request. This strategy is known as proactive caching or prefetching. It is a technique in which selected information is cached before it is actually needed. In comparison, past constructive caching strategies showed high data overhead in terms of computing costs. Therefore, with the use of Markov chain model, the aim of this work is to address the above problems by an efficient user future position movement prediction strategy. For modeling of the proposed system to evaluate the feasibility of accessing information on the network for location-based applications, the client-server queuing model is used in this chapter. The observational findings indicate substantial improvements in caching efficiency to previous caching policies that did not use prefetch module.

An Efficient Markov Chain Model Development based Prefetching in Location-Based Services

Communication between mobile clients and database servers in wireless environment suffers from; the user’s movement, disconnected modes, lots of data updates, low battery power, cache size limitation, and bandwidth limitation Caching is used in wireless environment to overcome these challenges The aim of this effort is to present enhanced invalidation policy that cooperates with a new cache replacement technique by using genetic programming to select the items that will be removed from the cache for improving data access in the wireless environment Cooperation between servers and mobile clients to enhance data availability Each mobile client Collects data like access probability, size, and next validation time and uses these parameters in a genetic programming method for selecting cached items to be removed when the cache is full The experiments were carried using NS2 software to evaluate the efficiency of the suggested policy, and the results are compared with existing cache policies algorithms The experiments have shown that the proposed policy outperfomed the LRU by 24% in byte hit ratio, and 11% in cache hit ratio It is concluded that the presented policy achieves well than other policies

An Improved Cache Invalidation Policy in Wireless Environment Cooperate with Cache Replacement Policy Based on Genetic Programming

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

In the mobile environment, the movement of users, disconnected modes, many data updates, power battery consumption, limited cache size, and limited bandwidth impose significant challenges to information access. Caching is considered one of the most important concepts to deal with these challenges. There are two general topics related to the client cache policy: cache invalidation method keeps data in the cache up to date; and cache replacement method chooses the cached item(s) which should be deleted from the cache when the cache is full. The aim of this work is to propose a new technique for cache replacement in a mobile database that takes into consideration the impact of invalidation time for enhancing data availability in the mobile environment by using genetic programming. In this case, each client collects information for every cached item in the cache like access probability, cached document size, validation time and uses these factors in a fitness function to determine cached items that will be removed from the cache. The experiments were performed using Network Simulator 2 to evaluate the effectiveness of the proposed approach, and the results are compared with the existing cache replacement algorithms. It is concluded that the proposed approach performs significantly better than other approaches.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-net.2017.0261

Amr G. El-Shnawy

Papers

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

Proactive cache replacement technique for mobile networks based on genetic programming