scholarly journals Caching and Placement for In-Network Caching in Device-to-Device Communications

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Somayeh Soleimani ◽  
Xiaofeng Tao
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Content Delivery ◽  
Base Stations ◽  
D2d Communications ◽  
Dual Decomposition ◽  
Placement Problem ◽  
Content Discovery ◽  
Device To Device ◽  
Promising Solution

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.

scholarly journals Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2449 ◽  
Author(s):  
Wenpeng Jing ◽  
Xiangming Wen ◽  
Zhaoming Lu ◽  
Haijun Zhang
Keyword(s):  
Content Delivery ◽  
Decision Time ◽  
Base Stations ◽  
Joint Optimization ◽  
Resources Allocation ◽  
User Association ◽  
Placement Problem ◽  
Content Caching ◽  
Backhaul Link ◽  
Content Placement

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.

scholarly journals Clustering-based device-to-device discovery and content delivery in wireless networks

2021 ◽  
Vol 2 (2) ◽  
pp. 21-33
Author(s):  
Tolga Girici ◽  
Ahmet Cihat Kazez
Keyword(s):  
Recent Literature ◽  
Memory Capacity ◽  
Network Capacity ◽  
Content Delivery ◽  
Device Discovery ◽  
Content Discovery ◽  
Term Evolution ◽  
Device To Device ◽  
Cache Placement

Device-to-device (D2D) cache placement and content delivery is a recent technology that exploits idle memory capacity of mobile devices and promises to fulfill users' content needs with very low delay and without using the scarce cellular network capacity. Recent literature on D2D caching mostly concentrated on optimal cache placement and mostly disregarded the required discovery mechanisms and the accompanying overhead. In this work we propose a clustering-based procedure that is used to cache content at the helper nodes along with advertisement and discovery procedures for content delivery. We implement a Long Term Evolution (LTE)-based simulation setup to evaluate the proposed schemes. Numerical results reveal that the clustering-based user and content discovery significantly improves cellular offloading and reduces the discovery overhead with a minimal sacrifice from delay.

scholarly journals Simulated annealing method for equilibrium placement problem

2021 ◽  
pp. 152-158
Author(s):  
Igor Kozin ◽  
Natalia Maksyshko ◽  
Yaroslav Tereshko
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Simulated Annealing Algorithm ◽  
Optimal Solution ◽  
Placement Problem ◽  
Fragmentary Structure ◽  
Simulating Annealing ◽  
Set Of Permutations ◽  
Annealing Algorithm ◽  
The Traveling Salesman Problem

The paper proposes a modification of the simulated annealing algorithm as applied to problems that have a fragmented structure. An algorithm for simulating annealing for the traveling salesman problem is considered and its applicability to the optimization problem on a set of permutations is shown. It is proved that the problem of equilibrium placement of point objects on a plane has a fragmentary structure and, therefore, reduces to an optimization problem on a set of permutations. The results of numerical experiments for various types of algorithms for finding the optimal solution in the equilibrium placement problem are presented.

scholarly journals Joint Placement and Device Association of UAV Base Stations in IoT Networks

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2157 ◽  
Author(s):  
Ashfaq Ahmed ◽  
Muhammad Awais ◽  
Tallha Akram ◽  
Selman Kulac ◽  
Musaed Alhussein ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Cost Effective ◽  
Low Complexity ◽  
Base Stations ◽  
Large Area ◽  
Significant Research ◽  
Minimum Number ◽  
Efficient Scheme

Drone base stations (DBSs) have received significant research interest in recent years. They provide a flexible and cost-effective solution to improve the coverage, connectivity, quality of service (QoS), and energy efficiency of large-area Internet of Things (IoT) networks. However, as DBSs are costly and power-limited devices, they require an efficient scheme for their deployment in practical networks. This work proposes a realistic mathematical model for the joint optimization problem of DBS placement and IoT users’ assignment in a massive IoT network scenario. The optimization goal is to maximize the connectivity of IoT users by utilizing the minimum number of DBS, while satisfying practical network constraints. Such an optimization problem is NP-hard, and the optimal solution has a complexity exponential to the number of DBSs and IoT users in the network. Furthermore, this work also proposes a linearization scheme and a low-complexity heuristic to solve the problem in polynomial time. The simulations are performed for a number of network scenarios, and demonstrate that the proposed heuristic is numerically accurate and performs close to the optimal solution.

scholarly journals Optimal Resource Management and Binary Power Control in Network-Assisted D2D Communications for Higher Frequency Reuse Factor

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 251 ◽  
Author(s):  
Devarani Ningombam ◽  
Seokjoo Shin
Keyword(s):  
Resource Management ◽  
Computational Complexity ◽  
Power Control ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Frequency Reuse ◽  
System Throughput ◽  
Greedy Heuristic ◽  
Fractional Frequency Reuse ◽  
D2d Communications

Device-to-device (D2D) communications can be adopted as a promising solution to attain high quality of service (QoS) for a network. However, D2D communications generates harmful interference when available resources are shared with traditional cellular users (CUs). In this paper, network architecture for the uplink resource management issue for D2D communications underlaying uplink cellular networks is proposed. We develop a fractional frequency reuse (FFR) technique to mitigate interference induced by D2D pairs (DPs) to CUs and mutual interference among DPs in a cell. Then, we formulate a sum throughput optimization problem to achieve the QoS requirements of the system. However, the computational complexity of the optimization problem is very high due to the exhaustive search for a global optimal solution. In order to reduce the complexity, we propose a greedy heuristic search algorithm for D2D communications so as to find a sub-optimal solution. Moreover, a binary power control scheme is proposed to enhance the system throughput by reducing overall interference. The performance of our proposed scheme is analyzed through extensive numerical analysis using Monte Carlo simulation. The results demonstrate that our proposed scheme provides significant improvement in system throughput with the lowest computational complexity.

A new algorithm for finding CRM-model coefficients

2019 ◽  
Vol 5 (3) ◽  
pp. 164-185 ◽  
Author(s):  
Alexander D. Bekman ◽  
Sergey V. Stepanov ◽  
Alexander A. Ruchkin ◽  
Dmitry V. Zelenin
Keyword(s):  
Approximate Solution ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Complex Form ◽  
Approximate Solutions ◽  
The Other ◽  
Programming Algorithm ◽  
Stochastic Algorithms ◽  
Large Set ◽  
Flow Rates

The quantitative evaluation of producer and injector well interference based on well operation data (profiles of flow rates/injectivities and bottomhole/reservoir pressures) with the help of CRM (Capacitance-Resistive Models) is an optimization problem with large set of variables and constraints. The analytical solution cannot be found because of the complex form of the objective function for this problem. Attempts to find the solution with stochastic algorithms take unacceptable time and the result may be far from the optimal solution. Besides, the use of universal (commercial) optimizers hides the details of step by step solution from the user, for example&nbsp;— the ambiguity of the solution as the result of data inaccuracy.<br> The present article concerns two variants of CRM problem. The authors present a new algorithm of solving the problems with the help of “General Quadratic Programming Algorithm”. The main advantage of the new algorithm is the greater performance in comparison with the other known algorithms. Its other advantage is the possibility of an ambiguity analysis. This article studies the conditions which guarantee that the first variant of problem has a unique solution, which can be found with the presented algorithm. Another algorithm for finding the approximate solution for the second variant of the problem is also considered. The method of visualization of approximate solutions set is presented. The results of experiments comparing the new algorithm with some previously known are given.

scholarly journals Algebraic Solution to Constrained Bi-Criteria Decision Problem of Rating Alternatives through Pairwise Comparisons

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 303
Author(s):  
Nikolai Krivulin
Keyword(s):  
Decision Problem ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Sufficient Conditions ◽  
Approximation Error ◽  
Optimal Solution ◽  
Algebraic Solution ◽  
Pairwise Comparisons ◽  
Logarithmic Scale ◽  
Idempotent Algebra

We consider a decision-making problem to evaluate absolute ratings of alternatives from the results of their pairwise comparisons according to two criteria, subject to constraints on the ratings. We formulate the problem as a bi-objective optimization problem of constrained matrix approximation in the Chebyshev sense in logarithmic scale. The problem is to approximate the pairwise comparison matrices for each criterion simultaneously by a common consistent matrix of unit rank, which determines the vector of ratings. We represent and solve the optimization problem in the framework of tropical (idempotent) algebra, which deals with the theory and applications of idempotent semirings and semifields. The solution involves the introduction of two parameters that represent the minimum values of approximation error for each matrix and thereby describe the Pareto frontier for the bi-objective problem. The optimization problem then reduces to a parametrized vector inequality. The necessary and sufficient conditions for solutions of the inequality serve to derive the Pareto frontier for the problem. All solutions of the inequality, which correspond to the Pareto frontier, are taken as a complete Pareto-optimal solution to the problem. We apply these results to the decision problem of interest and present illustrative examples.

scholarly journals Efficient Placement of Service Function Chains in Cloud Computing Environments

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 323
Author(s):  
Marwa A. Abdelaal ◽  
Gamal A. Ebrahim ◽  
Wagdy R. Anis
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Response Time ◽  
Optimization Problem ◽  
Service Providers ◽  
Virtual Network ◽  
Placement Problem ◽  
Service Function ◽  
Network Functions ◽  
Bandwidth Consumption

The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.

scholarly journals Quit When You Can: Efficient Evaluation of Ensembles by Optimized Ordering

2021 ◽  
Vol 17 (4) ◽  
pp. 1-20
Author(s):  
Serena Wang ◽  
Maya Gupta ◽  
Seungil You
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Combinatorial Optimization Problem ◽  
Joint Optimization ◽  
Early Stopping ◽  
Time Approximation ◽  
Approximation Bound ◽  
Evaluation Time ◽  
Speed Up ◽  
Real World Problems

Given a classifier ensemble and a dataset, many examples may be confidently and accurately classified after only a subset of the base models in the ensemble is evaluated. Dynamically deciding to classify early can reduce both mean latency and CPU without harming the accuracy of the original ensemble. To achieve such gains, we propose jointly optimizing the evaluation order of the base models and early-stopping thresholds. Our proposed objective is a combinatorial optimization problem, but we provide a greedy algorithm that achieves a 4-approximation of the optimal solution under certain assumptions, which is also the best achievable polynomial-time approximation bound. Experiments on benchmark and real-world problems show that the proposed Quit When You Can (QWYC) algorithm can speed up average evaluation time by 1.8–2.7 times on even jointly trained ensembles, which are more difficult to speed up than independently or sequentially trained ensembles. QWYC’s joint optimization of ordering and thresholds also performed better in experiments than previous fixed orderings, including gradient boosted trees’ ordering.

scholarly journals Formal Verification of Authentication and Service Authorization Protocols in 5G-Enabled Device-to-Device Communications Using ProVerif

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1608
Author(s):  
Ed Kamya Kiyemba Edris ◽  
Mahdi Aiash ◽  
Jonathan Loo
Keyword(s):  
Service Providers ◽  
Security Analysis ◽  
Mobile Network ◽  
Network Services ◽  
Control Mechanisms ◽  
D2d Communications ◽  
Fifth Generation ◽  
Device To Device ◽  
Pi Calculus ◽  
Authentication And Authorization

Device-to-Device (D2D) communications will be used as an underlay technology in the Fifth Generation mobile network (5G), which will make network services of multiple Service Providers (SP) available anywhere. The end users will be allowed to access and share services using their User Equipments (UEs), and thus they will require seamless and secured connectivity. At the same time, Mobile Network Operators (MNOs) will use the UE to offload traffic and push contents closer to users relying on D2D communications network. This raises security concerns at different levels of the system architecture and highlights the need for robust authentication and authorization mechanisms to provide secure services access and sharing between D2D users. Therefore, this paper proposes a D2D level security solution that comprises two security protocols, namely, the D2D Service security (DDSec) and the D2D Attributes and Capability security (DDACap) protocols, to provide security for access, caching and sharing data in network-assisted and non-network-assisted D2D communications scenarios. The proposed solution applies Identity-based Encryption (IBE), Elliptic Curve Integrated Encryption Scheme (ECIES) and access control mechanisms for authentication and authorization procedures. We formally verified the proposed protocols using ProVerif and applied pi calculus. We also conducted a security analysis of the proposed protocols.

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