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Journal articles on the topic 'Mobile computing. Transaction systems (Computer systems)'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Xie, Qingqing, Fan Dong, and Xia Feng. "ECLB: Edge-Computing-Based Lightweight Blockchain Framework for Mobile Systems." Security and Communication Networks 2021 (April 28, 2021): 1–15. http://dx.doi.org/10.1155/2021/5510586.

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The blockchain technology achieves security by sacrificing prohibitive storage and computation resources. However, in mobile systems, the mobile devices usually offer weak computation and storage resources. It prohibits the wide application of the blockchain technology. Edge computing appears with strong resources and inherent decentralization, which can provide a natural solution to overcoming the resource-insufficiency problem. However, applying edge computing directly can only relieve some storage and computation pressure. There are some other open problems, such as improving confirmation latency, throughput, and regulation. To this end, we propose an edge-computing-based lightweight blockchain framework (ECLB) for mobile systems. This paper introduces a novel set of ledger structures and designs a transaction consensus protocol to achieve superior performance. Moreover, considering the permissioned blockchain setting, we specifically utilize some cryptographic methods to design a pluggable transaction regulation module. Finally, our security analysis and performance evaluation show that ECLB can retain the security of Bitcoin-like blockchain and better performance of ledger storage cost in mobile devices, block mining computation cost, throughput, transaction confirmation latency, and transaction regulation cost.

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Klingemann, Justus, Thomas Tesch, and Jürgen Wäsch. "Cooperative Data Management and its Application to Mobile Computing." International Journal of Cooperative Information Systems 06, no. 03n04 (1997): 341–65. http://dx.doi.org/10.1142/s0218843097000161.

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Mobile computing and workgroup computing are emerging technologies which have so far been treated independently. Current approaches to support cooperative work neglect the special characteristics of mobile environments like limited bandwidth or temporary disconnection. On the other hand, approaches to support disconnected operation rely on the assumption that the degree of data-sharing is low which is obviously not appropriate for cooperative work. In this paper, we utilize the COACT cooperative transaction model to provide support for parallel activities in mobile environments. We present a system architecture that is able to cope with the special characteristics of mobile environments and a formal framework for the consistent information exchange between mobile users. The paper shows how the COACT history merge algorithm reduces conflicts by exploiting operation semantics and offering consistent sequences of operations. We believe that our new approach is a viable solution to the growing demand for cooperation in mobile environments.

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3

Ali, Ihtisham, and Susmit Bagchi. "A Comparative Study and Algorithmic Analysis of Workflow Decomposition in Distributed Systems." International Journal of Grid and High Performance Computing 11, no. 1 (2019): 71–100. http://dx.doi.org/10.4018/ijghpc.2019010105.

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Workflow is an essential mechanism for the automation of processes in distributed transactional systems, including mobile distributed systems. The workflow modeling enables the composition of process activities along with respective conditions, data flow and control flow dependencies. The workflow partitioning methods are used to create sub-partitions by grouping processes on the basis of activities, data flow and control flow dependencies. Mobile distributed systems consisting of heterogeneous computing devices require optimal workflow decomposition. In general, the workflow partitioning is a NP-complete problem. This article presents a comparative study and detailed analysis of workflow decomposition techniques based on graphs, petri nets and topological methods. A complete taxonomy of the basic decomposition techniques is presented. A detailed qualitative and quantitative analysis of these decomposition techniques are explained. The comparative analysis presented in this article provides an insight to inherent algorithmic complexities of respective decomposition approaches. The qualitative parametric analysis would help in determining the suitability of workflow applicability in different computing environments involving static and dynamic nodes. Furthermore, the authors have presented a novel framework for workflow decomposition based on multiple parametric parameters for mobile distributed systems.

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Fadelelmoula, Ashraf Ahmed. "Exploiting Cloud Computing and Web Services to Achieve Data Consistency, Availability, and Partition Tolerance in the Large-Scale Pervasive Systems." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 15 (2021): 74. http://dx.doi.org/10.3991/ijim.v15i15.22517.

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This article presents a new comprehensive approach to realize a sufficient trade-off between the CAP properties (i.e., consistency, availability, and partition tolerance) in the large-scale pervasive information systems. To achieve these critical properties, the capabilities of both cloud computing and web services were exploited in developing the components of the proposed approach. These components include a cloud-based replication architecture for ensuring high data availability and achieving partition tolerance, a web services-based middleware for maintaining the eventual consistency, and a data caching scheme to enable the mobile computing elements to conduct update transactions during the disconnection periods. The evaluation of the performance aspects revealed that the proposed approach is able to achieve a load balance, lower propagation delay, and higher cache hit ratio, as compared to other baseline approaches.

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Fu, Jinhua, Wenhui Zhou, Mixue Xu, Xueming Si, Chao Yuan, and Yongzhong Huang. "New public blockchain protocol based on sharding and aggregate signatures." Journal of High Speed Networks 27, no. 1 (2021): 83–99. http://dx.doi.org/10.3233/jhs-210653.

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Existing blockchains, especially public blockchains, face the challenges of scalability which means the processing capacity will not get better with the addition of nodes, making it somewhat infeasible for mobile computing applications. Some improved technologies are known to speed up processing capacity by shrinking the consensus group, increasing the block capacity and/or shortening the block interval. Even these solutions are met with major problems such as storage limitations and weak security. To face the realistic application scenarios for blockchain technology in the mobile realm, we propose a new public blockchain designed based on sharding, aggregate signature and cryptographic sortition which we call SAC. In SAC, the transaction rate increases with the number of shards while the length of the consensus signature is a constant. Meanwhile, in SAC, the assignment of consensus representatives is controlled by a verifiable random function, which can effectively solve the problem of centralized consensus. In addition, this paper analyzes the performance of SAC to give adequate comparison with other sharding technologies while also giving a rational security analysis. Our experimental results clearly show the potential applicability of this novel blockchain protocol to in mobile computation.

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Chitra, K., and Al-Dahoud Ali. "Prioritized Transaction Management for Mobile Computing Systems." International Journal of Intelligent Computing Research 2, no. 4 (2011): 175–79. http://dx.doi.org/10.20533/ijicr.2042.4655.2011.0023.

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7

Jain, Ashish. "Transaction Processing in Mobile Database Systems." SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology 7, no. 02 (2015): 87–92. http://dx.doi.org/10.18090/samriddhi.v7i2.8631.

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In a mobile computing environment, a potentially large number of mobile and fixed users may simultaneously access shared data; therefore, there is a need to provide a means to allow concurrent management of transactions. Specific characteristics of mobile environments make traditional transaction management techniques no longer appropriate. This is due the fact that the ACID properties of transactions are not simply followed, in particular the consistency property. Thus, transaction management models adopting weaker form of consistency are needed and these models can now tolerate a limited amount of consistency. In this paper we have proposed (execution framework based on common ground shared by most of mobile transaction models found in the literature and investigate it under different execution strategies. More over, the effects of the fixed host transaction are identified and included in the evaluation The integration between wired and wireless environments confirms that the execution strategy is critical for the performance of a system. Neither MHS nor FHS are optimal in all situations and the performance penalties and wasted wireless resources can be substantial. A combined strategy CHS at least matches the best performance of the FHS and MHS and shows better performance than both in many cases.

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8

Skehin, Nicholas, and Jaewoo Chung. "Mobile computing systems and applications." IEEE Pervasive Computing 10, no. 3 (2011): 80–83. http://dx.doi.org/10.1109/mprv.2011.53.

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9

Lim, J. B., and A. R. Hurson. "Transaction processing in mobile, heterogeneous database systems." IEEE Transactions on Knowledge and Data Engineering 14, no. 6 (2002): 1330–46. http://dx.doi.org/10.1109/tkde.2002.1047771.

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10

Tu, M., P. Li, L. Xiao, I. L. Yen, and F. B. Bastani. "Replica placement algorithms for mobile transaction systems." IEEE Transactions on Knowledge and Data Engineering 18, no. 7 (2006): 954–70. http://dx.doi.org/10.1109/tkde.2006.114.

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11

Schiller, J. "Review: Mobile Commerce and Wireless Computing Systems." Computer Journal 47, no. 2 (2004): 272–73. http://dx.doi.org/10.1093/comjnl/47.2.272.

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12

Kulik, Lars. "Mobile Computing Systems Programming: A Graduate Distributed Computing Course." IEEE Distributed Systems Online 8, no. 5 (2007): 4. http://dx.doi.org/10.1109/mdso.2007.27.

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13

Ellis, Carla Schlatter. "Controlling Energy Demand in Mobile Computing Systems." Synthesis Lectures on Mobile and Pervasive Computing 2, no. 1 (2007): 1–89. http://dx.doi.org/10.2200/s00089ed1v01y200704mpc002.

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14

R. Vincent, Olufunke, Olusegun Folorunso, Adio Taofiki Akinwale, and Adebayo D. Akinde. "Transaction Flow in Card Payment Systems Using Mobile Agents." Interdisciplinary Journal of Information, Knowledge, and Management 5 (2010): 153–66. http://dx.doi.org/10.28945/1153.

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15

Wang, Feng, Ge Bao Shan, Yong Chen, et al. "Identity Authentication Security Management in Mobile Payment Systems." Journal of Global Information Management 28, no. 1 (2020): 189–203. http://dx.doi.org/10.4018/jgim.2020010110.

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Mobile payment is a new payment method offering users mobility, reachability, compatibility, and convenience. But mobile payment involves great uncertainty and risk given its electronic and wireless nature. Therefore, biometric authentication has been adopted widely in mobile payment in recent years. However, although technology requirements for secure mobile payment have been met, standards and consistent requirements of user authentication in mobile payment are not available. The flow management of user authentication in mobile payment is still at its early stage. Accordingly, this paper proposes an anonymous authentication and management flow for mobile payment to support secure transaction to prevent the disclosure of users' information and to reduce identity theft. The proposed management flow integrates transaction key generation, encryption and decryption, and matching to process users' personal information and biometric characteristics based on mobile equipment authentication carrier.

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16

Pu, Haitao, Jinjiao Lin, Yanwei Song, and Fasheng Liu. "Adaptive Device Context Based Mobile Learning Systems." International Journal of Distance Education Technologies 9, no. 1 (2011): 44–56. http://dx.doi.org/10.4018/jdet.2011010103.

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Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for mobile devices to adapt to e-learning is presented. To provide device-independence mobile learning services, a context-aware mobile learning approach is proposed. Firstly, the formal definitions of contexts and their influence on mobile learning services, including device contexts NCxt, matrix of information transmission parameters S, the degree of influence of the context NCxt on information transmission parameters Q, and adaptation coefficient E, are given. By using this approach, the mobile learning system is constructed. In an example using this approach, the authors detect the contextual environment of mobile computing and adapt the mobile learning services to the learners’ devices automatically.

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17

Sun, Hui, Ying Yu, Kewei Sha, and Bendong Lou. "mVideo: Edge Computing Based Mobile Video Processing Systems." IEEE Access 8 (2020): 11615–23. http://dx.doi.org/10.1109/access.2019.2963159.

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18

Qiu, Xinyu, Linbo Zhai, and Hua Wang. "Time-Minimized Offloading for Mobile Edge Computing Systems." IEEE Access 7 (2019): 135439–47. http://dx.doi.org/10.1109/access.2019.2941825.

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19

Kumar Madria, Sanjay, Mukesh Mohania, Sourav S. Bhowmick, and Bharat Bhargava. "Mobile data and transaction management." Information Sciences 141, no. 3-4 (2002): 279–309. http://dx.doi.org/10.1016/s0020-0255(02)00178-0.

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20

Zhao, Xianlong, Kexin Yang, Qimei Chen, et al. "Deep learning based mobile data offloading in mobile edge computing systems." Future Generation Computer Systems 99 (October 2019): 346–55. http://dx.doi.org/10.1016/j.future.2019.04.039.

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21

Huang, Su-Zhen, Min Wu, and Yong-Hua Xiong. "Mobile Transparent Computing to Enable Ubiquitous Operating Systems and Applications." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 1 (2014): 32–39. http://dx.doi.org/10.20965/jaciii.2014.p0032.

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Mobile devices have emerged as an indispensable part of our daily life, one that has resulted in an increased demand for mobile devices to be able to access the Internet and obtain a variety of network services. However, mobile devices are often constrained by limited storage, huge power consumption, and low processing capability. This paper presents a new computing mode, mobile transparent computing (MTC), which combines ubiquitous mobile networks with transparent computing, to address the above challenges and possibly to enable a new world of ubiquitous operating systems (OSes) and applications with the following characteristics: (1) Mobile devices with no OSes pre-installed are able to load and boot multiple OSes on demand through a transparent network; (2) All resources, including the operating system (OS), applications, and user data, are stored on a transparent server (TS) rather than a mobile terminal, and can be streamed to be executed on mobile devices in small execution blocks; (3) All the personalized services (applications and data) can be synchronized to any other devices with the same user credential. Specifically, we propose a Pre OS technique, which can achieve feature (1) in the MTC model by initializing the mobile device and driving a network interface card (NIC) prior to OS loading, thereby transferring the needed OS streaming block to the mobile device. Experimental results conducted on the tablet demo-board with the model OK6410 based on the ARM11 architecture demonstrate that the Pre OS is able to support remote boot and streaming execution for both Android and Linux OS with satisfactory performance.

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22

Suh, Hyo-Joong, Junggab Son, and Kyungtae Kang. "Trustworthiness in Mobile Cyber-Physical Systems." Applied Sciences 11, no. 4 (2021): 1676. http://dx.doi.org/10.3390/app11041676.

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As they continue to become faster and cheaper, devices with enhanced computing and communication capabilities are increasingly incorporated into diverse objects and structures in the physical environment [...]

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23

Kayan, E. "An Evaluation of Real-Time Transaction Management Issues in Mobile Database Systems." Computer Journal 42, no. 6 (1999): 501–10. http://dx.doi.org/10.1093/comjnl/42.6.501.

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24

GUPTA, SUNIL KUMAR, R. K. CHAUHAN, and PARVEEN KUMAR. "A MINIMUM-PROCESS COORDINATED CHECKPOINTING PROTOCOL FOR MOBILE COMPUTING SYSTEMS." International Journal of Foundations of Computer Science 19, no. 04 (2008): 1015–38. http://dx.doi.org/10.1142/s0129054108006108.

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Checkpoint is a designated place in a program at which normal process is interrupted specifically to preserve the status information necessary to allow resumption of processing at a later time. A checkpoint algorithm for mobile distributed systems needs to handle many new issues like: mobility, low bandwidth of wireless channels, lack of stable storage on mobile nodes, disconnections, limited battery power and high failure rate of mobile nodes. These issues make traditional checkpointing techniques unsuitable for such environments. Minimum-process coordinated checkpointing is an attractive approach to introduce fault tolerance in mobile distributed systems transparently. This approach is domino-free, requires at most two checkpoints of a process on stable storage, and forces only a minimum number of processes to checkpoint. But, it requires extra synchronization messages, blocking of the underlying computation or taking some useless checkpoints. In this paper, we design a minimum-process checkpointing algorithm for mobile distributed systems, where no useless checkpoint is taken. We reduce the blocking of processes by allowing the processes to do their normal computations, send messages and receive selective messages during their blocking period.

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Behera, Itishree, and Chita Ranjan Tripathy. "Performance modelling and analysis of mobile grid computing systems." International Journal of Grid and Utility Computing 5, no. 1 (2014): 11. http://dx.doi.org/10.1504/ijguc.2014.058244.

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Mahenge, Michael P. J., Chunlin Li, and Camilius A. Sanga. "Mobile Edge Computing." International Journal of Mobile Computing and Multimedia Communications 10, no. 3 (2019): 23–46. http://dx.doi.org/10.4018/ijmcmc.2019070102.

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The overwhelming growth of resource-intensive and latency-sensitive applications trigger challenges in legacy systems of mobile cloud computing (MCC) architecture. Such challenges include congestion in the backhaul link, high latency, inefficient bandwidth usage, insufficient performance, and quality of service (QoS) metrics. The objective of this study was to find out the cost-efficient design that maximizes resource utilization at the edge of the mobile network which in return minimizes the task processing costs. Thus, this study proposes a cooperative mobile edge computing (coopMEC) to address the aforementioned challenges in MCC architecture. Also, in the proposed approach, resource-intensive jobs can be unloaded from users' equipment to MEC layer which is potential for enhancing performance in resource-constrained mobile devices. The simulation results demonstrate the potential gain from the proposed approach in terms of reducing response delay and resource consumption. This, in turn, improves performance, QoS, and guarantees cost-effectiveness in meeting users' demands.

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Wang, Feng, Jie Xu, Xin Wang, and Shuguang Cui. "Joint Offloading and Computing Optimization in Wireless Powered Mobile-Edge Computing Systems." IEEE Transactions on Wireless Communications 17, no. 3 (2018): 1784–97. http://dx.doi.org/10.1109/twc.2017.2785305.

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Zhang, Jiang, Zhenfeng Zhang, and Hui Guo. "Towards Secure Data Distribution Systems in Mobile Cloud Computing." IEEE Transactions on Mobile Computing 16, no. 11 (2017): 3222–35. http://dx.doi.org/10.1109/tmc.2017.2687931.

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Ahn, JinHo, Sung-Gi Min, and Chong-Sun Hwang. "A causal message logging protocol for mobile nodes in mobile computing systems." Future Generation Computer Systems 20, no. 4 (2004): 663–86. http://dx.doi.org/10.1016/s0167-739x(03)00130-4.

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30

Chen, Ying, Yongchao Zhang, and Xin Chen. "Dynamic Service Request Scheduling for Mobile Edge Computing Systems." Wireless Communications and Mobile Computing 2018 (September 13, 2018): 1–10. http://dx.doi.org/10.1155/2018/1324897.

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Nowadays, mobile services (applications) running on terminal devices are becoming more and more computation-intensive. Offloading the service requests from terminal devices to cloud computing can be a good solution, but it would put a high burden on the network. Edge computing is an emerging technology to solve this problem, which places servers at the edge of the network. Dynamic scheduling of offloaded service requests in mobile edge computing systems is a key issue. It faces challenges due to the dynamic nature and uncertainty of service request patterns. In this article, we propose a Dynamic Service Request Scheduling (DSRS) algorithm, which makes request scheduling decisions to optimize scheduling cost while providing performance guarantees. The DSRS algorithm can be implemented in an online and distributed way. We present mathematical analysis which shows that the DSRS algorithm can achieve arbitrary tradeoff between scheduling cost and performance. Experiments are also carried out to show the effectiveness of the DSRS algorithm.

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31

Borcea, Cristian, Shiwen Mao, and Jian Tang. "Editorial: Mobile and Ubiquitous Systems: Computing, Networking and Services." Mobile Networks and Applications 25, no. 2 (2019): 457–58. http://dx.doi.org/10.1007/s11036-019-01371-y.

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32

Ma, Xiao, Zie Wang, Sheng Zhou, Haoyu Wen, and Yin Zhang. "Intelligent Healthcare Systems Assisted by Data Analytics and Mobile Computing." Wireless Communications and Mobile Computing 2018 (July 3, 2018): 1–16. http://dx.doi.org/10.1155/2018/3928080.

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It is entering an era of big data, which facilitated great improvement in various sectors. Particularly, assisted by wireless communications and mobile computing, mobile devices have emerged with a great potential to renovate the healthcare industry. Although the advanced techniques will make it possible to understand what is happening in our body more deeply, it is extremely difficult to handle and process the big health data anytime and anywhere. Therefore, data analytics and mobile computing are significant for the healthcare systems to meet many technical challenges and problems that need to be addressed to realize this potential. Furthermore, the advanced healthcare systems have to be upgraded with new capabilities such as machine learning, data analytics, and cognitive power for providing human with more intelligent and professional healthcare services. To explore recent advances and disseminate state-of-the-art techniques related to data analytics and mobile computing on designing, building, and deploying novel technologies, to enable intelligent healthcare services and applications, this paper presents the detailed design for developing intelligent healthcare systems assisted by data analytics and mobile computing. Moreover, some representative intelligent healthcare applications are discussed to show that data analytics and mobile computing are available to enhance the performance of the healthcare services.

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33

Beloudane, Amel, and Ghalem Belalem. "Towards an Efficient Management of Mobile Cloud Computing Services based on Multi Agent Systems." Journal of Information Technology Research 8, no. 3 (2015): 59–72. http://dx.doi.org/10.4018/jitr.2015070104.

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Today, there is an increase of using mobile smart devices. These devices can have an effective access to information and benefit of many applications in the Cloud. Cloud Computing (CC) exploits its full potential with many difficulties due to its inherent problems such as resource scarcity, intermittent network connectivity, and mobility. Mobile Cloud Computing (MCC) can treat these problems by executing mobile applications on external resource providers to the mobile device for high-performance and scalability of mobile applications. This paper discusses the authors' approach on mobile cloud computing environment. This analysis permits to select the most appropriate service satisfied SLA while reducing energy consumption and increasing its availability in the Cloud without deteriorating performance and energy consumption. For that, the authors proposed a dynamic, efficient and equilibrated model based on multi-agent system and Top-K technology.

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Hsu, Ching-Hsien, Shangguang Wang, Yan Zhang, and Anna Kobusinska. "Mobile Edge Computing." Wireless Communications and Mobile Computing 2018 (June 27, 2018): 1–3. http://dx.doi.org/10.1155/2018/7291954.

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35

Umar, Amjad. "Computer Aided Planning for Wireless Systems." International Journal of Business Data Communications and Networking 8, no. 1 (2012): 56–67. http://dx.doi.org/10.4018/jbdcn.2012010104.

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Information and communication technology (ICT) managers in the modern enterprises face a bewildering array of decisions regarding planning of new systems, integration of new systems with existing ones, securing the ICT assets, and administrating the resulting complex ICT systems. The rapid introduction of wireless systems (mobile computing and wireless communications) in the business and government settings is further exasperating the situation, particularly in the developing countries. A Computer Aided Planner (Planner), part of the UN eNabler Toolset, has been developed to quickly and effectively produce detailed strategic plans for a wide range of egovernment services with particular attention to wireless systems. This paper presents a high level overview of this effort.

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36

Park, Taesoon, Namyoon Woo, and Heon Y. Yeom. "An efficient recovery scheme for fault-tolerant mobile computing systems." Future Generation Computer Systems 19, no. 1 (2003): 37–53. http://dx.doi.org/10.1016/s0167-739x(02)00095-x.

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37

Zhou, Xiang, Jilin Zhang, Jian Wan, Li Zhou, Zhenguo Wei, and Juncong Zhang. "Scheduling-Efficient Framework for Neural Network on Heterogeneous Distributed Systems and Mobile Edge Computing Systems." IEEE Access 7 (2019): 171853–63. http://dx.doi.org/10.1109/access.2019.2954897.

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Aliyu, Ahmed, Abdul Hanan Abdullah, Omprakash Kaiwartya, et al. "Mobile Cloud Computing: Taxonomy and Challenges." Journal of Computer Networks and Communications 2020 (July 1, 2020): 1–23. http://dx.doi.org/10.1155/2020/2547921.

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Mobile cloud computing (MCC) holds a new dawn of computing, where the cloud users are attracted to multiple services through the Internet. MCC has a qualitative, flexible, and cost-effective delivery platform for providing services to mobile cloud users with the aid of the Internet. Due to the advantage of the delivery platform, several studies have been conducted on how to address different issues in MCC. The issues include energy efficiency in MCC, secured MCC, user-satisfied applications and Quality of Service-aware MCC (QoS). In this context, this paper qualitatively reviews different proposed MCC solutions. Therefore, taxonomy for MCC is presented considering major themes of research including energy-aware, security, applications, and QoS-aware developments. Each of these themes is critically investigated with comparative assessments considering recent advancements. Analysis of metrics and implementation environments used for evaluating the performance of existing techniques are presented. Finally, some open research issues and future challenges are identified based on the critical and qualitative assessment of literature for researchers in this field.

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39

Kuang, Zhufang, Linfeng Li, Jie Gao, Lian Zhao, and Anfeng Liu. "Partial Offloading Scheduling and Power Allocation for Mobile Edge Computing Systems." IEEE Internet of Things Journal 6, no. 4 (2019): 6774–85. http://dx.doi.org/10.1109/jiot.2019.2911455.

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Faye, Sébastien, Walter Bronzi, Ibrahim Tahirou, and Thomas Engel. "Characterizing user mobility using mobile sensing systems." International Journal of Distributed Sensor Networks 13, no. 8 (2017): 155014771772631. http://dx.doi.org/10.1177/1550147717726310.

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Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches can, for instance, provide an enhanced user experience based on different sets of built-in sensors that follow every user action and identify its environment. Monitoring solutions such as these, which are becoming more and more common, allows us to assess human behavior and movement at different levels. In this article, extended from previous work, we focus on the concept of human mobility and explore how we can exploit a dataset collected opportunistically from multiple participants. In particular, we study how the different sensor groups present in most commercial smart devices can be used to deliver mobility information and patterns. In addition to traditional motion sensors that are obviously important in this field, we are also exploring data from physiological and environmental sensors, including new ways of displaying, understanding, and analyzing data. Furthermore, we detail the need to use methods that respect the privacy of users and investigate the possibilities offered by network traces, including Wi-Fi and Bluetooth communication technologies. We finally offer a mobility assistant that can represent different user characteristics anonymously, based on a combination of Wi-Fi, activity data, and graph theory.

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41

Chiang, Yi-Han, Tianyu Zhang, and Yusheng Ji. "Joint Cotask-Aware Offloading and Scheduling in Mobile Edge Computing Systems." IEEE Access 7 (2019): 105008–18. http://dx.doi.org/10.1109/access.2019.2931336.

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Wu, Hao, Hui Tian, Gaofeng Nie, and Pengtao Zhao. "Wireless Powered Mobile Edge Computing for Industrial Internet of Things Systems." IEEE Access 8 (2020): 101539–49. http://dx.doi.org/10.1109/access.2020.2995649.

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43

Taesoon Park, Namyoon Woo, and H. Y. Yeom. "An efficient optimistic message logging scheme for recoverable mobile computing systems." IEEE Transactions on Mobile Computing 1, no. 4 (2002): 265–77. http://dx.doi.org/10.1109/tmc.2002.1175540.

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Mitra, Karan, Arkady Zaslavsky, and Christer Ahlund. "Context-Aware QoE Modelling, Measurement, and Prediction in Mobile Computing Systems." IEEE Transactions on Mobile Computing 14, no. 5 (2015): 920–36. http://dx.doi.org/10.1109/tmc.2013.155.

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45

Meng, Xianling, Wei Wang, Yitu Wang, Vincent K. N. Lau, and Zhaoyang Zhang. "Closed-Form Delay-Optimal Computation Offloading in Mobile Edge Computing Systems." IEEE Transactions on Wireless Communications 18, no. 10 (2019): 4653–67. http://dx.doi.org/10.1109/twc.2019.2926465.

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Han, Rui, Yongqing Wen, Lin Bai, Jianwei Liu, and Jinho Choi. "Rate Splitting on Mobile Edge Computing for UAV-Aided IoT Systems." IEEE Transactions on Cognitive Communications and Networking 6, no. 4 (2020): 1193–203. http://dx.doi.org/10.1109/tccn.2020.3012680.

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47

Bhalla, Subhash. "Evolving a model of transaction management with embedded concurrency control for mobile database systems." Information and Software Technology 45, no. 9 (2003): 587–96. http://dx.doi.org/10.1016/s0950-5849(03)00045-4.

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48

Layton, Charles F., Michael J. Christodoulou, Joseph T. Jackson, and Jonathan L. Turner. "Lessons Learned in the Development of Mobile Electronic Performance Support Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39, no. 4 (1995): 268–72. http://dx.doi.org/10.1177/154193129503900410.

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There are a number of interacting constraints that affect the development of mobile electronic performance support systems (Gery, 1991). For example, users frequently want the resources of a desktop computer in a palm-sized box. Hardware technology, however, dictates that the greater the resources, the larger the device. Mobile electronic performance support systems are frequently initiated as a means to ‘automate’ manual processes. However, such processes must be redesigned to match the capabilities and requirements of mobile computing platforms. As a final example, the desktop conventions of “new, open, and save” used when working with documents are not necessarily the best conventions for mobile applications. This paper identifies many of the constraints involved in developing mobile computing applications and discusses them in the context of applications.

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Kharma, Qasem, Nidal M. Turab, Qusai Shambour, and Mohammad Hassan. "Secure Cloud-Mediator Architecture for Mobile-Government using RBAC and DUKPT." International Journal of Interactive Mobile Technologies (iJIM) 14, no. 04 (2020): 44. http://dx.doi.org/10.3991/ijim.v14i04.11075.

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<p class="0abstract">Smart mobile devices and cloud computing are widely used today. While mobile and portable devices have different capabilities, architectures, operating systems, and communication channels than one another, government data are distributed over heterogeneous systems. This paper proposes a 3-tier mediation framework providing single application to manage all governmental services. The framework is based on private cloud computing for adapting the content of Mobile-Government (M-Government) services using Role-Based Access Control (RBAC) and Derive Unique Key Per Transaction (DUKPT). The 3-layers in the framework are: presence, integration, and homogenization. The presence layer is responsible for adapting the content with regard to four contexts: device, personal, location, and connectivity contexts. The integration layer, which is hosted in a private cloud server, is responsible for integrating heterogeneous data sources. The homogenization layer is responsible for converting data into XML format. The flexibility of the mediation and XML provides an adaptive environment to stream data based on the capabilities of the device that sends the query to the system.</p>

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Zarandi, Sheyda, and Hina Tabassum. "Delay Minimization in Sliced Multi-Cell Mobile Edge Computing (MEC) Systems." IEEE Communications Letters 25, no. 6 (2021): 1964–68. http://dx.doi.org/10.1109/lcomm.2021.3051558.

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