Abstract-The landscape towards 5G wireless communication is currently unclear, and, despite the efforts of academia and industry in evolving traditional cellular networks, the enabling technology for 5G is still obscure. This paper puts forward a network paradigm towards next-generation cellular networks, targeting to satisfy the explosive demand for mobile data while minimizing energy expenditures. The paradigm builds on two principles; namely caching and multicast. On one hand, caching policies disperse popular content files at the wireless edge, e.g., pico-cells and femto-cells, hence shortening the distance between content and requester. On other hand, due to the broadcast nature of wireless medium, requests for identical files occurred at nearby times are aggregated and served through a common multicast stream. To better exploit the available cache space, caching policies are optimized with concerns on multicast transmissions. We show that the multicast-aware caching problem is NP-Hard and develop solutions with performance guarantees using randomized-rounding techniques. Trace-driven numerical results show that in presence of massive demand for delay tolerant content, combining caching and multicast can indeed reduce energy costs. The gains over existing caching schemes are 19% when users tolerate delay of three minutes, increasing further with the steepness of content access pattern.
The deployment of small cells is expected to gain huge momentum in the near future, as a solution for managing the skyrocketing mobile data demand growth. Local caching of popular files at the small cell base stations has been recently proposed, aiming at reducing the traffic incurred when transferring the requested content from the core network to the users. In this paper, we propose and analyze a novel caching approach that can achieve significantly lower traffic compared to the traditional caching schemes. Our cache design policy carefully takes into account the fact that an operator can serve the requests for the same file that happen at nearby times via a single multicast transmission. The latter incurs less traffic as the requested file is transmitted to the users only once, rather than with many unicast transmissions. Systematic experiments demonstrate the effectiveness of our approach, as compared to the existing caching schemes.The authors are with the Department of Electrical and Computer Engineering, University of Thessaly, Volos, Greece. Emails: {kopoular, giosifid, vsourlas, leandros} @uth.gr 1 The so-called multimedia broadcast multicast service (MBMS) was incorporated in Rel. 6, and more recently the respective enhanced version eMBMS in Rel. 9. Our analysis is generic and holds for other multicast/broadcast technologies, such as DVB-H, DVB-D, as well.
Abstract-Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. ISPs have the opportunity to deploy private edge-clouds in their infrastructure to generate additional revenue by providing ultra-low latency applications to local users. We envision a rapid increase in the number of such applications for "edge" networks in the near future with virtual/augmented reality (VR/AR), networked gaming, wearable cognitive assistance, autonomous driving and IoT analytics having already been proposed for edgeclouds instead of the central clouds to improve performance. This raises new challenges as the complexity of the resource allocation problem for multiple services with latency deadlines (i.e., which service to place at which node of the edge-cloud in order to satisfy the latency constraints) becomes significant. In this paper, we propose a set of practical, uncoordinated strategies for service placement in edge-clouds. Through extensive simulations using both synthetic and real-world trace data, we demonstrate that uncoordinated strategies can perform comparatively well with the optimal placement solution, which satisfies the maximum amount of user requests.
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