Qos-aware mobile service optimization in multi-access mobile edge computing environments

With the rapid development of mobile Internet technologies and various new service services such as virtual reality (VR) and augmented reality (AR), users’ demand for network quality of service (QoS) is getting higher and higher. To solve the problems of high load and low latency in-network services, this paper proposes a data caching strategy based on a multi-access mobile edge computing environment. Based on the MEC collaborative caching framework, an SDN controller is introduced into the MEC collaborative caching framework, a joint cache optimization mechanism based on data caching and computational migration is constructed, and the user-perceived time-lengthening problem in the data caching strategy is solved by a joint optimization algorithm based on an improved heuristic genetic algorithm and simulated annealing. Meanwhile, this paper proposes a multi-base station collaboration-based service optimization strategy to solve the problem of collaboration of computation and storage resources due to multiple mobile terminals and multiple smart base stations. For the problem that the application service demand in MEC server changes due to time, space, requests and other privacy, an application service optimization algorithm based on the Markov chain of service popularity is constructed, and a deep deterministic strategy (DDP) based on deep reinforcement learning is also used to minimize the average delay of computation tasks in the cluster while ensuring the energy consumption of MEC server, which improves the accuracy of application service cache updates in the system as well as reducing the complexity of service updates. The experimental results show that the proposed data caching algorithm weighs the cache space of user devices, the average transfer latency of acquiring data resources is effectively reduced, and the proposed service optimization algorithm can improve the quality of user experience.     

Fuzzy online location management in mobile computing environments

This paper presents a new approach, namely Intelligent Fuzzy Online Location Management Strategy (IFOLMS), based on Fuzzy clustering techniques to solve the mobile location management problem. Using a Fuzzy location estimator in this technique, mobile users’ past movements are used in making future paging decisions by the network. IFOLMS has the potential to lead to massive savings in the number of network signal transactions that must be made to locate users. Performance of the proposed approach has been measured by using several test networks; it shows promising results — around 50% reduction in network cost — when compared to many of the existing location management techniques (including GSM). Results also provide new insights into the mobility management problem and its associated performance issues.     

Secondary user relations in emerging mobile computing environments

Mobile technologies are enabling access to information in diverse environments, and are exposing a wider group of individuals to said technology. Therefore, this paper proposes that a wider view of user relations than is usually considered in information systems research is required. Specifically, we examine the potential effects of emerging mobile technologies on end-user relations with a focus on the ‘secondary user’, those who are not intended to interact directly with the technology but are intended consumers of the technology's output. For illustration, we draw on a study of a U.K. regional Fire and Rescue Service and deconstruct mobile technology use at Fire Service incidents. Our findings provide insights, which suggest that, because of the nature of mobile technologies and their context of use, secondary user relations in such emerging mobile environments are important and need further exploration.     

移动计算环境下的通用安全支付系统框架

移动代理在未来的移动商务中具有举足轻重的地位,它能提供更好的灵活性和性能。但也面临着许多新的安全问题。以移动代理和SEMOPS模型为基础,结合现有的移动支付协议,抽象出移动支付系统通用的业务模块,提出了一种新的移动计算环境下通用安全移动支付系统框架。     

连接中断计算环境下移动数据的处理模型

无线网络中断和弱连接现象,常导致用户在访问远程数据时访问中断和数据丢失,并正成为移动计算发展的一个瓶颈。基于这种现状,提出一种在无线网络出现连接暂时中断时移动计算环境下移动数据的处理模型,以解决上述问题。为提高用户访问数据的可靠性,即在出现网络连接中断时使用户能够在离线情况下继续操作且不会丢失数据,该模型在移动终端提供语义缓存功能,并能在连接恢复时立即执行被滞后的操作。     

移动计算环境中基于广播的数据缓存策略

在研究了数据广播频率的变化对缓存策略的影响之后,提出以移动客户机（Mobile Client,MC）从广播中读取数据的平均响应时间为标准,来决定是否缓存该数据项。其优点是可以避免每次访问这些数据项等待较长时间,同时也可降低移动客户机缓存管理的代价,提高其工作性能。     

移动计算环境下数据复制一致性研究

通过对移动计算环境下已复制数据一致性的研究,提出了一种新的数据复制控制协议。该协议对已复制数据库对象的读操作或写操作等临时信息进行探索,使单副本可串行化和最终一致性两个标准可以同时得到保证。文章最后还对协议的正确性进行了分析。     

Navigation integration of a mobile robot in dynamic environments

This article presents a design and experimental study of navigation integration of an intelligent mobile robot in dynamic environments. The proposed integration architecture is based on the virtual‐force concept, by which each navigation resource is assumed to exert a virtual force on the robot. The resultant force determines how the robot will move. Reactive behavior and proactive planning can both be handled in a simple and uniform manner using the proposed integration method. A real‐time motion predictor is employed to enable the mobile robot to deal in advance with moving obstacles. A grid map is maintained using on‐line sensory data for global path planning, and a bidirectional algorithm is proposed for planning the shortest path for the robot by using updated grid‐map information. Therefore, the mobile robot has the capacity to both learn and adapt to variations. To implement the whole navigation system efficiently, a blackboard model is used to coordinate the computation on board the vehicle. Simulation and experimental results are presented to verify the proposed design and demonstrate smooth navigation behavior of the intelligent mobile robot in dynamic environments. ©1999 John Wiley & Sons, Inc.     

移动边缘计算环境中面向机器学习的计算迁移策略

针对物联网(IoT)数据源的多样化、数据的非独立同分布性、边缘设备计算能力和能耗的异构性,提出一种集中学习和联邦学习共存的移动边缘计算(MEC)网络计算迁移策略.首先,建立与集中学习、联邦学习都关联的计算迁移系统模型,考虑了集中学习、联邦学习模型产生的网络传输延迟、计算延迟以及能耗;然后,以系统平均延迟为优化目标、以能...     

A provably secure lightweight authentication protocol in mobile edge computing environments

The Journal of Supercomputing - Mobile edge computing can meet the needs of users in real time by pushing cloud resources, such as computing, network, and storage, to the edge of a mobile network....     

Exploiting data mining techniques for broadcasting data in mobile computing environments

Mobile computers can be equipped with wireless communication devices that enable users to access data services from any location. In wireless communication, the server-to-client (downlink) communication bandwidth is much higher than the client-to-server (uplink) communication bandwidth. This asymmetry makes the dissemination of data to client machines a desirable approach. However, dissemination of data by broadcasting may induce high access latency in case the number of broadcast data items is large. We propose two methods aiming to reduce client access latency of broadcast data. Our methods are based on analyzing the broadcast history (i.e., the chronological sequence of items that have been requested by clients) using data mining techniques. With the first method, the data items in the broadcast disk are organized in such a way that the items requested subsequently are placed close to each other. The second method focuses on improving the cache hit ratio to be able to decrease the access latency. It enables clients to prefetch the data from the broadcast disk based on the rules extracted from previous data request patterns. The proposed methods are implemented on a Web log to estimate their effectiveness. It is shown through performance experiments that the proposed rule-based methods are effective in improving the system performance in terms of the average latency as well as the cache hit ratio of mobile clients.     

Dynamic cloud resource management for efficient media applications in mobile computing environments

Single-instruction-set architecture (Single-ISA) heterogeneous multi-core processors (HMP) are superior to Symmetric Multi-core processors in performance per watt. They are popular in many aspects of the Internet of Things, including mobile multimedia cloud computing platforms. One Single-ISA HMP integrates both fast out-of-order cores and slow simpler cores, while all cores are sharing the same ISA. The quality of service (QoS) is most important for virtual machine (VM) resource management in multimedia mobile computing, particularly in Single-ISA heterogeneous multi-core cloud computing platforms. Therefore, in this paper, we propose a dynamic cloud resource management (DCRM) policy to improve the QoS in multimedia mobile computing. DCRM dynamically and optimally partitions shared resources according to service or application requirements. Moreover, DCRM combines resource-aware VM allocation to maximize the effectiveness of the heterogeneous multi-core cloud platform. The basic idea for this performance improvement is to balance the shared resource allocations with these resources requirements. The experimental results show that DCRM behaves better in both response time and QoS, thus proving that DCRM is good at shared resource management in mobile media cloud computing.     

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.     

DewSim: A trace-driven toolkit for simulating mobile device clusters in Dew computing environments

Dew computing is an emerging computing paradigm, which aims at minimizing the dependency over existing internetwork back-haul, ie, being dependent on processing resources offered by remote servers. Smartphones and tablets ubiquity and powerful computing hardware motivated researchers to investigate the way of providing Dew computing services by exploiting the aggregated capabilities of devices in a vicinity, a smart device cluster. Consequently, research on resource management is necessary to learn how to scavenge resources from such a cluster, deal with devices heterogeneity, limitations, and dynamic resource availability. Simulation is commonly practiced for studying resource management in other distributed computing research fields, specially due to the complexity involved in the set up of experiments. However, a free-to-use purpose specific toolkit for studying smart device clusters do not exist or have been documented. Current simulation efforts do not allow researchers to faithfully represent key singularities of such environment, which are energy depletion and nondedicated nature of computing resources. We propose a trace-based toolkit built on modular software artifacts to speed up research in resource management techniques in Dew environments. A trace-driven methodology is adopted to assure practical value of simulated scenarios. The toolkit comprises a device profiler application for Android to capture generic battery and CPU traces from real devices, a profile mixer to create user interaction baseline traces through generic ones, and an extensible engine to simulate the execution of workloads configurable via text files. Verification and validation tests were run to show correctness and reliability of our simulation approach.     

Locating objects in mobile computing

In current distributed systems, the notion of mobility is emerging in many forms and applications. Mobility arises naturally in wireless computing since the location of users changes as they move. Besides mobility in wireless computing, software mobile agents are another popular form of moving objects. Locating objects, i.e., identifying their current location, is central to mobile computing. We present a comprehensive survey of the various approaches to the problem of storing, querying, and updating the location of objects in mobile computing. The fundamental techniques underlying the proposed approaches are identified, analyzed, and classified along various dimensions     

Transaction pseudonyms in mobile environments

Network Operators start to offer formerly hidden services such as location service, messaging services and presence services. This fosters the development of a new class of innovative context aware applications that are operated by third party application providers. However, without the implementation of proper privacy protection mechanisms, location and presence information, that is processed by third party application providers, may also imply severe risks to users. If no privacy protection is foreseen, the user’s identity could be used maliciously which renders such applications dangerous. To protect the user’s sensitive data such as location information we propose a novel service architecture which fosters the development of innovative applications that brings together internet applications with telco services. An underlying privacy enhancing mechanism that is based on the notion of pseudonyms allows even untrusted third party application providers to access sensitive data provided by telco services such as location, presence or messaging services. Due to their high security, pseudonyms guarantee that the user’s identity is kept secret towards the untrusted application providers. Due to its low computational complexity this pseudonym generation scheme can also be implemented on devices such as mobile phones and digital assistants with only little computational power and restricted memory capabilities. To illustrate our approach, we demonstrate a transportation ticket application that implements the proposed service architecture. This application allows the use of transportation tickets which are extended by the location-tracking functionality. Similar to the well known paper based transportation tickets our solution supports anonymity of users even if the ticket application “knows” the location of the holder. Oliver Jorns is a researcher at the Telecommunications Research Center in Vienna and is also a Lecturer at the University of Vienna. Oliver Jung is employed as a Senior Researcher at the Telecommunications Research Center Vienna. He is also member of ISO/IEC JTC1 SC27 (IT security techniques). Gerald Quirchmayr is Professor at the Institute for Computer Science and Business Informatics at the University of Vienna and since January 2005 he heads the Department of Distributed and Multimedia Systems, Faculty of Computer Science, at the University of Vienna.     

Trust-based security in pervasive computing environments

Traditionally, stand-alone computers and small networks rely on user authentication and access control to provide security. These physical methods use system-based controls to verify the identity of a person or process, explicitly enabling or restricting the ability to use, change, or view a computer resource. However, these strategies are inadequate for the increased flexibility that distributed networks such as the Internet and pervasive computing environments require because such systems lack central control and their users are not all predetermined. Mobile users expect to access locally hosted resources and services anytime and anywhere, leading to serious security risks and access control problems. We propose a solution based on trust management that involves developing a security policy, assigning credentials to entities, verifying that the credentials fulfill the policy, delegating trust to third parties, and reasoning about users' access rights. This architecture is generally applicable to distributed systems but geared toward pervasive computing environments     

Pull-based recommendations in mobile environments

In the field of Context-Aware Recommendation Systems (CARS), only static contextual information is usually considered. However, the dynamic contextual information would very helpful in mobile computing scenarios. Despite this interest, the design and implementation of flexible and generic frameworks to support an easy development of context-aware mobile recommendation systems have been relatively unexplored. In this paper, we describe a framework that facilitates the development of CARS for mobile environments. We mainly focus on the development of the elements needed to support pull-based recommendations and the experimental evaluation of the proposed system.