Search

Under demanding operational conditions such as traffic surges, coverage issues, and low latency requirements, terrestrial networks may become inadequate to provide the expected service levels to users and applications. Moreover, when natural disasters or physical calamities occur, the existing network infrastructure may collapse, leading to formidable challenges for emergency communications in the area served. In order to provide wireless connectivity as well as facilitate a capacity boost under transient high service load situations, a substitute or auxiliary fast-deployable network is needed. Unmanned Aerial Vehicle (UAV) networks are well suited for such needs thanks to their high mobility and flexibility. In this work, we consider an edge network consisting of UAVs equipped with wireless access points. These software-defined network nodes serve a latency-sensitive workload of mobile users in an edge-to-cloud continuum setting. We investigate prioritization-based task offloading to support prioritized services in this on-demand aerial network. To serve this end, we construct an offloading management optimization model to minimize the overall penalty due to priority-weighted delay against task deadlines. Since the defined assignment problem is NP-hard, we also propose three heuristic algorithms as well as a branch and bound style quasi-optimal task offloading algorithm and investigate how the system performs under different operating conditions by conducting simulation-based experiments. Moreover, we made an open-source contribution to Mininet-WiFi to have independent Wi-Fi mediums, which were compulsory for simultaneous packet transfers on different Wi-Fi mediums.

For providing wireless connectivity and facilitating a capacity boost under transient high service load situations, a substitute or auxiliary fast-deployable network is instrumental. Unmanned Aerial Vehicle (UAV) networks are well suited for such needs owing to their high mobility and agility. This paper considers a software-defined edge network consisting of UAVs equipped with wireless access points, which serve mobile users with latency-sensitive workload in an edge-to-cloud continuum setting. It investigates the task offloading paradigm to provide prioritized services via this on-demand aerial network. Accordingly, a task processing optimization model is defined to minimize the overall penalty calculated based on priority-weighted delay values against a priori defined task deadlines. Since the defined assignment problem is NP-hard, tailored heuristic models are proposed and evaluated to study how the system performs under different operating conditions.

Multimedia content transmission heavily taxes network resources and puts a significant burden on wireless systems in terms of capacity and energy consumption. In this context, device-to-device (D2D) paradigm has a utilitarian value to alleviate the network burden by utilizing short-range transmissions with less energy cost. For the realization of proper D2D networking, caching in devices is essential. Additionally, caching needs to operate efficiently with the aim of realizing network-wide energy improvements. To this end, we study multimedia caching in cellular D2D networks and propose an energy prioritized D2D caching (EPDC) algorithm in this work. We also investigate the optimal caching policy in that system setting. The impact of device capacity and D2D transmission range on energy consumption is studied by focusing on different operation modes such as D2D and base station transmissions. According to the simulation results, EPDC algorithm has substantial energy-efficiency gains over the commonly utilized Least Recently Used (LRU) algorithm and content-based caching algorithms PDC and SXO. For larger D2D transmission ranges, this improvement becomes more evident.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Future Internet is going to be shaped by networked multimedia services with exploding video traffic becoming the dominant payload. That evolution requires a remedial shift from the connection-oriented architecture to a content-centric one. Another technique to address this capacity crunch is to improve spectral utilization through new networking paradigms at the wireless network edge. To this end, Device-to-Device (D2D) communications has the potential for boosting the capacity and energy efficiency for content-centric networking. To design and implement efficient content-centric D2D networks, rigorous content modeling and in-network caching mechanisms based on such models are crucial. In this work, we develop a multidimensional content model based on popularity, chunking and layering, and devise caching schemes through this model. Our main motivation is to improve the system performance via our caching strategies. The numerical analysis shows the interplay among different system parameters and performance metrics: while our schemes perform slightly poorer in terms of system goodput, they also decrease the system energy expenditure. Overall, this improvement dominates the loss in the goodput, leading to greater energy efficiency compared to the commonly-used caching technique Least Recently Used (LRU).

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Device-to-device (D2D) transmissions in wireless edge networks are promising for optimizing system-wide energy consumption and improving system service capacity. Cooperative content caching similarly serves efficiency goals for data-intensive applications in edge networks. In this work, we propose two cooperative cache replacement algorithms in D2D networks to support these techniques: i) distance-based ii) priority-class based. Video content dissemination in an edge network is our main use-case. In such content traffic, video characteristics have a significant impact on the system behavior. Therefore, we also investigate the effect of content scene change dynamics in our system. Distance based cooperation outperforms LRU, MIN-ACC and SXO in terms of goodput while priority-class based approach consumes less energy than MIN-ACC with almost the same consumption as LRU, especially under fast changing scene regime. Besides, it is energy-wise slightly more rewarding than SXO for the fastest-changing scene case.

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., A sizeable software defined network with a single controller responsible for all forwarding elements is potentially failure-prone and inadequate for dynamic network loads. To this end, having multiple controllers improves resilience and distributes network control overhead. However, when there is a disruption in the control plane, a rapid and performant controller-switch assignment is critical, which is a challenging technical question. In this work, we propose a proactive switch assignment approach in case of controller failures using a genetic algorithm based heuristic that considers controller load distribution, reassignment cost and probability of failure. Moreover, we compare the performance of our scheme with random and greedy algorithms. Experiment results show that our proposed PREFCP framework has better performance in terms of probability of failure and controller load distribution

SDN brings new opportunities to alleviate the existing security deficiencies of traditional networks. However, it also introduces new issues, a primary one being the vulnerabilities related to data and control plane communications. This work presents a security architecture to address security problems regarding data exchange in software-defined networks. To this end, a cryptographic key generation application is proposed to generate certificates that are used for securing communication of SDN entities (controller, switch, and application). We also provide an overview of related literature focusing on key elements in such architecture. In our model, TLS can be activated between SDN nodes to provide confidentiality, integrity, authentication, and authorization with special certificate fields. Besides, an integrated security module further strengthens the communication security by applying ACL, hardening TLS configuration and reducing the impact of private key hijacking. It also facilitates security administration tasks via per-channel activation/ deactivation of TLS protocol and monitoring of real-time security alarms.