1,124 research outputs found
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Cooperative Local Caching under Heterogeneous File Preferences
Local caching is an effective scheme for leveraging the memory of the mobile
terminal (MT) and short range communications to save the bandwidth usage and
reduce the download delay in the cellular communication system. Specifically,
the MTs first cache in their local memories in off-peak hours and then exchange
the requested files with each other in the vicinity during peak hours. However,
prior works largely overlook MTs' heterogeneity in file preferences and their
selfish behaviours. In this paper, we practically categorize the MTs into
different interest groups according to the MTs' preferences. Each group of MTs
aims to increase the probability of successful file discovery from the
neighbouring MTs (from the same or different groups). Hence, we define the
groups' utilities as the probability of successfully discovering the file in
the neighbouring MTs, which should be maximized by deciding the caching
strategies of different groups. By modelling MTs' mobilities as homogeneous
Poisson point processes (HPPPs), we analytically characterize MTs' utilities in
closed-form. We first consider the fully cooperative case where a centralizer
helps all groups to make caching decisions. We formulate the problem as a
weighted-sum utility maximization problem, through which the maximum utility
trade-offs of different groups are characterized. Next, we study two benchmark
cases under selfish caching, namely, partial and no cooperation, with and
without inter-group file sharing, respectively. The optimal caching
distributions for these two cases are derived. Finally, numerical examples are
presented to compare the utilities under different cases and show the
effectiveness of the fully cooperative local caching compared to the two
benchmark cases
A review of relay network on UAVS for enhanced connectivity
One of the best evolution in technology breakthroughs is the Unmanned Aerial Vehicle (UAV). This aerial system is able to perform the mission in an agile environment and can reach the hard areas to perform the tasks autonomously. UAVs can be used in post-disaster situations to estimate damages, to monitor and to respond to the victims. The Ground Control Station can also provide emergency messages and ad-hoc communication to the Mobile Users of the disaster-stricken community using this network. A wireless network can also extend its communication range using UAV as a relay. Major requirements from such networks are robustness, scalability, energy efficiency and reliability. In general, UAVs are easy to deploy, have Line of Sight options and are flexible in nature. However, their 3D mobility, energy constraints, and deployment environment introduce many challenges. This paper provides a discussion of basic UAV based multi-hop relay network architecture and analyses their benefits, applications, and tradeoffs. Key design considerations and challenges are investigated finding fundamental issues and potential research directions to exploit them. Finally, analytical tools and frameworks for performance optimizations are presented
Caching on Named Data Network: a Survey and Future Research
The IP-based system cause inefficient content delivery process. This inefficiency was attempted to be solved with the Content Distribution Network. A replica server is located in a particular location, usually on the edge router that is closest to the user. The user’s request will be served from that replica server. However, caching on Content Distribution Network is inflexible. This system is difficult to support mobility and conditions of dynamic content demand from consumers. We need to shift the paradigm to content-centric. In Named Data Network, data can be placed on the content store on routersthat are closest to the consumer. Caching on Named Data Network must be able to store content dynamically. It should be selectively select content that is eligible to be stored or deleted from the content storage based on certain considerations, e.g. the popularity of content in the local area. This survey paper explains the development of caching techniques on Named Data Network that are classified into main points. The brief explanation of advantages and disadvantages are presented to make it easy to understand. Finally, proposed the open challenge related to the caching mechanism to improve NDN performance
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