Energy Efficiency in Cache Enabled Small Cell Networks With Adaptive User Clustering

Using a network of cache enabled small cells, traffic during peak hours can be reduced considerably through proactively fetching the content that is most probable to be requested. In this paper, we aim at exploring the impact of proactive caching on an important metric for future generation networks, namely, energy efficiency (EE). We argue that, exploiting the correlation in user content popularity profiles in addition to the spatial repartitions of users with comparable request patterns, can result in considerably improving the achievable energy efficiency of the network. In this paper, the problem of optimizing EE is decoupled into two related subproblems. The first one addresses the issue of content popularity modeling. While most existing works assume similar popularity profiles for all users in the network, we consider an alternative caching framework in which, users are clustered according to their content popularity profiles. In order to showcase the utility of the proposed clustering scheme, we use a statistical model selection criterion, namely Akaike information criterion (AIC). Using stochastic geometry, we derive a closed-form expression of the achievable EE and we find the optimal active small cell density vector that maximizes it. The second subproblem investigates the impact of exploiting the spatial repartitions of users with comparable request patterns. After considering a snapshot of the network, we formulate a combinatorial optimization problem that enables to optimize content placement such that the used transmission power is minimized. Numerical results show that the clustering scheme enable to considerably improve the cache hit probability and consequently the EE compared with an unclustered approach. Simulations also show that the small base station allocation algorithm results in improving the energy efficiency and hit probability.Comment: 30 pages, 5 figures, submitted to Transactions on Wireless Communications (15-Dec-2016

NYS PROMISE Learning Community Group Concept Mapping: Fall 2016 Case Manager Experience - Final Report

Beginning in 2014, the Federal Government provided funding to New York State as part of an initiative to improve services that lead to sustainable outcomes for youth receiving Supplemental Security Income (SSI) benefits. As part of the NYS PROMISE initiative, Concept Systems, Inc. worked with the Learning Community to develop learning needs frameworks using the Group Concept Mapping methodology (GCM). The GCM projects gather, aggregates, and integrate the specific knowledge and opinions of the Learning Community members. This allows for their guidance and involvement in supporting NYS PROMISE as a viable community of practice. This work also increases the responsiveness of NYS PROMISE to the Learning Community members’ needs by inspiring discussion during the semi-annual in-person meetings. As of the end of year three, three GCM projects have been completed with the PROMISE Learning Community. These projects focused on Outreach and Recruitment Project 1), Case Management and Service Delivery (Project 2), and Case Manager Experience (Project 3). This report discusses the data collection method and participation in the Case Manager Experience GCM project, as well as providing graphics, statistical reports, and a summary of the analysis

Energy Efficiency and Quality of Services in Virtualized Cloud Radio Access Network

Cloud Radio Access Network (C-RAN) is being widely studied for soft and green fifth generation of Long Term Evolution - Advanced (LTE-A). The recent technology advancement in network virtualization function (NFV) and software defined radio (SDR) has enabled virtualization of Baseband Units (BBU) and sharing of underlying general purpose processing (GPP) infrastructure. Also, new innovations in optical transport network (OTN) such as Dark Fiber provides low latency and high bandwidth channels that can support C-RAN for more than forty-kilometer radius. All these advancements make C-RAN feasible and practical. Several virtualization strategies and architectures are proposed for C-RAN and it has been established that C-RAN offers higher energy efficiency and better resource utilization than the current decentralized radio access network (D-RAN). This project studies proposed resource utilization strategy and device a method to calculate power utilization. Then proposes and analyzes a new resource management and virtual BBU placement strategy for C-RAN based on demand prediction and inter-BBU communication load. The new approach is compared with existing state of art strategies with same input scenarios and load. The trade-offs between energy efficiency and quality of services is discussed. The project concludes with comparison between different strategies based on complexity of the system, performance in terms of service availability and optimization efficiency in different scenarios

A dual-role typology of multinational subsidiaries

This paper argues that, since a subsidiary is embedded in a dual context of both the MNE and the host environment, its strategic role should be assessed by its relative positions and contributions both within the knowledge networks of the MNE and the host country. Based on this, we develop a dual-role typology. The 369 multinational subsidiaries in our sample from China can be classified into as many as 12 out of the 16 conceptual groups of the typology. Our results indicate that dual activists (active both internally and externally) account for only 12% of the total sampled multinational subsidiaries while dual loners (inactive both internally and externally) reach 20%. The results from a larger sample by adding 113 minority foreign share firms show that external knowledge links are positively associated with local Chinese ownership. The central message from this paper is that a large proportion of foreign-invested firms in China are inactive in knowledge exchange either internally or externally or both. Managerial and policy implications are discussed

A Role-Based Taxonomy of Human Resource Organizations

[Excerpt] An empirically-derived classification (taxonomy) of human resource departments , based on a few fundamental roles played in organizations, was developed as an alternative to the mostly speculative existing typologies. Four types emerged: the strategic partner, the strategic advisor, the operational partner, and the operational administrator. The stability of the solution and the relationships with variables not used to generate it were found satisfactory. The types show some similarities with those identified in the literature

Proactive cloud management for highly heterogeneous multi-cloud infrastructures

Various literature studies demonstrated that the cloud computing paradigm can help to improve availability and performance of applications subject to the problem of software anomalies. Indeed, the cloud resource provisioning model enables users to rapidly access new processing resources, even distributed over different geographical regions, that can be promptly used in the case of, e.g., crashes or hangs of running machines, as well as to balance the load in the case of overloaded machines. Nevertheless, managing a complex geographically-distributed cloud deploy could be a complex and time-consuming task. Autonomic Cloud Manager (ACM) Framework is an autonomic framework for supporting proactive management of applications deployed over multiple cloud regions. It uses machine learning models to predict failures of virtual machines and to proactively redirect the load to healthy machines/cloud regions. In this paper, we study different policies to perform efficient proactive load balancing across cloud regions in order to mitigate the effect of software anomalies. These policies use predictions about the mean time to failure of virtual machines. We consider the case of heterogeneous cloud regions, i.e regions with different amount of resources, and we provide an experimental assessment of these policies in the context of ACM Framework

Corporate Real Estate Management: Evidence from German Companies

Based on a conceptual framework of factors representing and influencing corporate real estate management, this study is the first to be performed on the topic in Germany. The research shows that, despite their significant value and associated costs, real estate assets are at present seriously undermanaged by the vast majority of German companies. It seems that the international "bandwagon" toward active real estate management has not yet reached German firms. However, in some companies the function is evolving into a recognized management activity that requires a more formal and systematic approach.