User Movement and Content Placement Control with Optimization Problem for Content Delivery Services

Author(s):  
Yudai Mori ◽  
Takuji Tachibana
2021 ◽  
Author(s):  
Linh Nguyen

<pre>The paper addresses the problem of efficiently planning routes for multiple ground vehicles used in goods delivery services. Given popularity of today's e-commerce, particularly under the COVID-19 pandemic conditions, goods delivery services have been booming than ever, dominated by small-scaled (electric) bikes and promised by autonomous vehicles. However, finding optimal routing paths for multiple delivery vehicles operating simultaneously in order to minimize transportation cost is a fundamental but challenging problem. In this paper, it is first proposed to exploit the mixed integer programming paradigm to model the delivery routing optimization problem (DROP) for multiple simultaneously-operating vehicles given their energy constraints. The routing optimization problem is then solved by the multi-chromosome genetic algorithm, where the number of delivery vehicles can be optimized. The proposed approach was evaluated in a real-world experiment in which goods were expected to be delivered from a depot to 26 suburb locations in Canberra, Australia. The obtained results demonstrate effectiveness of the proposed algorithm.</pre>


2011 ◽  
pp. 278-295
Author(s):  
Irwin Boutboul ◽  
Dikran S. Meliksetian

n this chapter, we propose a new approach for content delivery services by meshing together the best of grid computing and peer-to-peer (P2P) computing. The goal is to design a secure, reliable, and scalable system for efficient and fast delivery of content. The system consists of a combination of nondedicated servers and peers to provide the proposed service. We describe the challenges of designing such a system and discuss possible solutions and trade-offs. We detail the necessary interlacing of grid and P2P feature to achieve the goal. We present a prototype that is built based on the proposed approach.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Somayeh Soleimani ◽  
Xiaofeng Tao

Caching content by users constitutes a promising solution to decrease the costly transmissions with going through the base stations (BSs). To improve the performance of in-network caching in device-to-device (D2D) communications, caching placement and content delivery should be jointly optimized. To this end, we jointly optimize caching decision and content discovery strategies by considering the successful content delivery in D2D links for maximizing the in-network caching gain through D2D communications. Moreover, an in-network caching placement problem is formulated as an integer nonlinear optimization problem. To obtain the optimal solution for the proposed problem, Lagrange dual decomposition is applied in order to reduce the complexity. Simulation results show that the proposed algorithm has a near-optimal performance, approaching that of the exhaustive search method. Furthermore, the proposed scheme has a notable in-network caching gain and an improvement in traffic offloading compared to that of other caching placement schemes.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 5277-5284 ◽  
Author(s):  
Chao Fang ◽  
Haipeng Yao ◽  
Zhuwei Wang ◽  
Pengbo Si ◽  
Yixin Chen ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2449 ◽  
Author(s):  
Wenpeng Jing ◽  
Xiangming Wen ◽  
Zhaoming Lu ◽  
Haijun Zhang

Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs’ cache tends to be small, while mobile users’ content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users’ data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.


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