Publications

Servicing Inelasticity, Leasing Resources and Pricing in 5G Networks

Authors: Apostolos Apostolaras, Kostas Chounos, Leandros Tassiulas and Thanasis Korakis

Conference: in proceedings of the 18th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOPT), Volos, Greece, 15-19 June 2020.

Abstract: We consider the problem for mobile network op-erators (MNOs) of leasing resources, servicing and pricingmobile users, in the context of 5G systems that facilitate theuse of software-defined radio access network (SD-RAN) andnetwork function virtualization (NFV) technologies. We studythe case where the service capability of a MNO cannot satisfythe total users’ demand who are characterized by inelasticbehavior against the servicing rate that they experience. TheMNO addresses this temporal depletion of its resources andacquires dynamically, through leasing, additional resources froman infrastructure provider (InP) to adequately comply with itsmobile users’ demand. We model and analyze the interactionsamong the MNO, and the users, as a Stackelberg game. Tomodel users’ inelastic behavior, we use a sigmoid utility function.Furthermore, we show the optimal pricing decisions when MNO’ssupplying capacity satisfies users’ demand. Given an excesson MNO’s supplying capacity, we employ the generalizedr-Lambert function to determine the optimal pricing. When MNO’ssupplying capacity is not ample, we determine, besides pricing,an approximation of the optimal amount of the additionalresources to purchase, given a leasing cost imposed by the InP. Aninteresting finding shows that the amount of additional resourcesto be purchased can be larger than the MNO’s minimumcapacity gap. Simulation and testbed experimentation validatethe feasibility of the proposed pricing and leasing scheme anddemonstrate its practical application.

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A Dynamic Pricing and Leasing Module for 5G Networks

Authors: K.Chounos, A. Apostolaras and T. Korakis

Conference: in proceedings of IEEE WF-5G 2020, 10 September – 10 October, 2020 Virtual Event Volos, Greece, 15-19 June 2020.

Abstract: In this paper, a novel framework for enablingdynamic Policy and Charging Rules in modern 5G multi-tenancyenvironments is designed and presented. More specifically, adap-tive pricing schemes are utilized by MNOs for instantiatingtailored slices, when the resources of a Mobile Network Operator(MNO) are insufficient to serve the connected users. A schemewhere an MNO seeks and leases additional resources from anInfrastructure Provider (InP) is examined in this paper. Theirnegotiation is modeled as a Service Level Agreement (SLA) andthe dynamic charging rules are implemented as an extension ofthe 5G Policy Charging Function (PCF). The analytical structureof the proposed architecture as well as all the methods and signalsdeveloped for MNO and InP collaboration, are described in thecontext of this work. Finally, extensive testbed experimentationproves proper functioning of the proposed framework, underboth UDP and TCP additional traffic demands.

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EVERUN - Enabling Power Consumption Monitoring in Underwater Networking Platforms

Authors: Giannis Kazdaridis, Stratos Keranidis, Polychronis Symeonidis, Paulo Sousa Dias, Pedro Gonçalves, Bruno Loureiro, Petrika Gjanci and Chiara Petrioli

Conference: ACM WinTech 2017, ACM Mobicom 2017, Snowbird, Utah, USA, 20 October 2017

Abstract: The energy restricted nature of underwater sensor networks directly affects the expected lifetime of autonomous deployments and limits the capabilities for long term underwater monitoring. Towards the goal of developing energy-efficient protocols and algorithms, researchers and equipment vendors require in-depth understanding of the power consumption characteristics of underwater hardware when deployed in-field. In this work, we introduce the EVERUN power monitoring framework, consisting of hardware and software components that were integrated with real equipment of the SUNRISE testbed facilities. Through the execution of a wide set of experiments under realistic conditions, we highlighted the limitations of model-based energy evaluation tools and characterized the energy efficiency performance of key protocols and mechanisms. The accuracy of the collected power data, along with the interesting derived findings, verified the applicability of our approach in evaluating the energy efficiency performance of proposed solutions.

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In-situ Power Consumption Meter for Sensor Networks supporting Extreme Dynamic Range

Authors: Giannis Kazdaridis, Ioannis Zographopoulos, Polychronis Symeonidis, Panagiotis Skrimponis, Thanasis Korakis and Leandros Tassiulas

Conference: ACM WinTech 2017, ACM Mobicom 2017, Snowbird, Utah, USA, 20 October 2017

Abstract: Typical wireless sensor devices feature an extreme power consumption range between their active and sleep states, thus requiring different hardware setups for measuring their expenditure with high accuracy. In this demo paper we present the NITOS dynamic ACM, an in-situ power meter that exploits auto-ranging methods to support high dynamic currents. Our implementation features 250 kSps of sampling rate, while attaining high precision in both the active and sleep states of the targeted device, by using two different shunt resistors that are alternated automatically with the aid of a high speed comparator. The acquired results indicate the smooth performance of our system as well as the high accuracy attained.