Fog-supported delay-constrained energy-saving live migration of VMs over multiPath TCP/IP 5G connections

The incoming era of the fifth-generation fog computing-supported radio access networks (shortly, 5G FOGRANs) aims at exploiting computing/networking resource virtualization, in order to augment the limited resources of wireless devices through the seamless live migration of virtual machines (VMs) toward nearby fog data centers. For this purpose, the bandwidths of the multiple wireless network interface cards of the wireless devices may be aggregated under the control of the emerging MultiPathTCP (MPTCP) protocol. However, due to the fading and mobility-induced phenomena, the energy consumptions of the current state-of-the-art VM migration techniques may still offset their expected benefits. Motivated by these considerations, in this paper, we analytically characterize and implement in software and numerically test the optimal minimum-energy settable-complexity bandwidth manager (SCBM) for the live migration of VMs over 5G FOGRAN MPTCP connections. The key features of the proposed SCBM are that: 1) its implementation complexity is settable on-line on the basis of the target energy consumption versus implementation complexity tradeoff; 2) it minimizes the network energy consumed by the wireless device for sustaining the migration process under hard constraints on the tolerated migration times and downtimes; and 3) by leveraging a suitably designed adaptive mechanism, it is capable to quickly react to (possibly, unpredicted) fading and/or mobility-induced abrupt changes of the wireless environment without requiring forecasting. The actual effectiveness of the proposed SCBM is supported by extensive energy versus delay performance comparisons that cover: 1) a number of heterogeneous 3G/4G/WiFi FOGRAN scenarios; 2) synthetic and real-world workloads; and, 3) MPTCP and wireless connections

Nearby live virtual machine migration using cloudlets and multipath TCP

A nearby virtual machine (VM) based cloudlet is proposed for mobile cloud computing (MCC) to enhance the performance of real-time resource-intensive mobile applications. Generally, when a mobile device (MD) discovers a cloudlet in the vicinity, it takes time to set up a VM inside the cloudlet before data offloading from the MD to the VM starts. The time between the discovery of the cloudlet and actual offloading of data is considered as the service initiation time. When multiple cloudlets are present in a nearby geographical location, initiating a service with each cloudlet may be frustrating for cloudlet users that moving from one location to another. In order to eliminate the delay caused by the service initiation time after moving away from the source cloudlet, this paper proposes a seamless live VM migration between neighbouring cloudlets. A seamless live VM migration is achieved with the prior knowledge of the migrating VM IP address in the destination cloudlet and more importantly with multip

A survey on mobility-induced service migration in the fog, edge, and related computing paradigms

The final publication is available at ACM via http://dx.doi.org/10.1145/3326540With the advent of fog and edge computing paradigms, computation capabilities have been moved toward the edge of the network to support the requirements of highly demanding services. To ensure that the quality of such services is still met in the event of users’ mobility, migrating services across different computing nodes becomes essential. Several studies have emerged recently to address service migration in different edge-centric research areas, including fog computing, multi-access edge computing (MEC), cloudlets, and vehicular clouds. Since existing surveys in this area focus on either VM migration in general or migration in a single research field (e.g., MEC), the objective of this survey is to bring together studies from different, yet related, edge-centric research fields while capturing the different facets they addressed. More specifically, we examine the diversity characterizing the landscape of migration scenarios at the edge, present an objective-driven taxonomy of the literature, and highlight contributions that rather focused on architectural design and implementation. Finally, we identify a list of gaps and research opportunities based on the observation of the current state of the literature. One such opportunity lies in joining efforts from both networking and computing research communities to facilitate future research in this area.Peer ReviewedPreprin

QoS-aware service continuity in the virtualized edge

5G systems are envisioned to support numerous delay-sensitive applications such as the tactile Internet, mobile gaming, and augmented reality. Such applications impose new demands on service providers in terms of the quality of service (QoS) provided to the end-users. Achieving these demands in mobile 5G-enabled networks represent a technical and administrative challenge. One of the solutions proposed is to provide cloud computing capabilities at the edge of the network. In such vision, services are cloudified and encapsulated within the virtual machines or containers placed in cloud hosts at the network access layer. To enable ultrashort processing times and immediate service response, fast instantiation, and migration of service instances between edge nodes are mandatory to cope with the consequences of user’s mobility. This paper surveys the techniques proposed for service migration at the edge of the network. We focus on QoS-aware service instantiation and migration approaches, comparing the mechanisms followed and emphasizing their advantages and disadvantages. Then, we highlight the open research challenges still left unhandled.publishe

Resource Management in Container-based Mobile Edge Computing

Mobile edge computing is a promising technology which provides support to time-sensitive applications by pushing centralized cloud processing capabilities to distributed Fog nodes. These fog nodes are deployed at one-hop distance from end-user and provide real-time data processing capabilities at the edge of network. Due to service provisioning at the edge of network, no congestion occurs at the core of network, quality of service (QoS) is improved and the overall network operational cost is significantly reduced. However, these nodes have limited capabilities such as processing, storage and coverage so, they face challenge of mobility support for a mobile user when continued service (i.e. zero downtime) is required during handovers between edge nodes. Furthermore, they also need an effective task allocation and resource management strategy to ensure smooth operation of edge services. Unlike traditional VM based environment in Fog Computing, this work explores lightweight Docker containers to deploy and migrate services. In this work, an interactive event-driven dashboard is developed for real-time edge node registration, system monitoring, service initiation and migration. Then, motivated by Fog Following Me, a couple of resource allocation schemes (i.e. algorithm-I & II) have been introduced to dynamically manage the compute resources among fog nodes. For smooth service operation and stable migration, an application profiling feature has been introduced which assigns the needed quota for an application requirement in terms of CPU, GPU and RAM. The developed system's performance is evaluated by conducting various experiments. The experimental results clearly demonstrate and verify the working feasibility of the whole system's operation in context of edge computing. However, the observed processing delays during service migration marks the limitation of Docker and suggest the need to use latest optimization tools to cut down the network delays and ensure zero-downtime service migration

HIP based mobility for Cloudlets

Computation offloading can be used to leverage the resources of nearby computers to ease the computational burden of mobile devices. Cloudlets are an approach, where the client's tasks are executed inside a virtual machine (VM) on a nearby computing element, while the client orchestrates the deployment of the VM and the remote execution in it. Mobile devices tend to move, and while moving between networks, their address is prone to change. Should a user bring their device close to a better performing Cloudlet host, migration of the original Cloudlet VM might also be desired, but their address is then prone to change as well. Communication with Cloudlets relies on the TCP/IP networking stack, which resolves address changes by terminating connections, and this seriously impairs the usefulness of Cloudlets in presence of mobility events. We surveyed a number of mobility management protocols, and decided to focus on Host Identity Protocol (HIP). We ported an implementation, HIP for Linux (HIPL), to the Android operating system, and assessed its performance by benchmarking throughput and delay for connection recovery during network migration scenarios. We found that as long as the HIPL hipfw-module, and especially the Local Scope Identifier (LSI) support was not used, the implementation performed adequately in terms of throughput. On the average, the connection recovery delays were tolerable, with an average recovery time of about 8 seconds when roaming between networks. We also found that with highly optimized VM synthesis methods, the recovery time of 8 seconds alone does not make live migration favourable over synthesizing a new VM. We found HIP to be an adequate protocol to support both client mobility and server migration with Cloudlets. Our survey suggests that HIP avoids some of the limitations found in competing protocols. We also found that the HIPL implementation could benefit from architectural changes, for improving the performance of the LSI support.Liikkuvassa tietojenkäsittelyssä laskennan ulkoistaminen on menetelmä, jolla voidaan käyttää ympäristössä olevien tietokoneiden resursseja keventämään mobiililaitteeseen kohdistuvaa laskennallista rasitusta. Cloudletit ovat eräs ratkaisu mobiililaskennan ulkoistamiseen, jossa laitteessa suoritettavia tehtäviä siirretään suoritettavaksi tietokoneessa ajettavaan virtuaalikoneeseen. Mobiililaite ohjaa virtuaalikoneen luomista ja siinä tapahtuvaa laskentaa verkon yli. Mobiililaitteen taipumus liikkua käyttäjänsä mukana aiheuttaa haasteita nykyisen TCP/IP protokollapinon joustavuudelle. Mobiililaitteen siirtyessä verkosta toiseen, on tyypillistä että sen IP-osoite vaihtuu. Mikäli mobiililaite siirtyy lähelle Cloudlet-isäntäkonetta, joka olisi resurssiensa ja tietoliikenneyhteyksiensä puolesta suotuisampi käyttäjän tarpeisiin, voi käyttäjän Cloudlet-virtuaalikoneen siirtäminen olla toivottavaa. Tällöin kuitenkin myös virtuaalikoneen osoite voi vaihtua. TCP/IP ratkaisee osoitteen vaihtumisen katkaisemalla yhteyden, mikä käyttäjien liikkuvuutta rajoittavana tekijänä tekee Cloudlet-ratkaisun käytöstä vähemmän houkuttelevaa. Tässä tutkielmassa tutustuimme joukkoon sopivaksi arvioimiamme liikkuvuutta tukevia protokollia, ja valitsimme niistä HIP -protokollan lähempää tarkastelua varten. Teimme HIP for Linux -protokollaohjelmistosta sovituksen Android-käyttöjärjestelmälle ja tutkimme sen soveltuvuutta liikkuvuuden tukemiseen mittaamalla sen avulla muodostetuilla yhteyksillä saavutettavia siirtonopeuksia sekä yhteyden palautumiseen kuluvaa aikaa osoitteenvaihdosten yhteydessä. Mikäli HIPL:in hipfw-moduuli, ja erityisesti sen LSI-tuki (IPv4-sovellusrajapinta) ei ollut käytössä, mittaustemme mukaan protokollatoteutus suoriutui Cloudlet-käyttöön riittävän hyvin siirtonopeuksien suhteen. Lisäksi yhteyksien palauttaminen osoitteenvaihdosten yhteydessä sujui siedettävässä ajassa, keskimäärin noin kahdeksassa sekunnissa. Hyvin optimoitujen Cloudlet-virtuaalikoneiden synteesimenetelmien vuoksi kahdeksan sekunnin toipumisaika yksinään ei tarjoa virtuaalikoneen siirtämisestä merkittävää etua uuden luomiseen nähden. HIP protokolla soveltuu yhteydenpitoon sekä mobiililaitteesta Cloudlet-isäntäkoneille, että Cloudlet-virtuaalikoneeseen; pienehkön kirjallisuuskatsauksen perusteella muita oleellisia protokollia hieman paremmin. Tunnistimme myös uudistamistarpeen HIPL-toteutuksen arkkitehtuurissa LSI-tuen suorituskyvyn parantamiseksi

Exploring traffic and QoS management mechanisms to support mobile cloud computing using service localisation in heterogeneous environments

In recent years, mobile devices have evolved to support an amalgam of multimedia applications and content. However, the small size of these devices poses a limit the amount of local computing resources. The emergence of Cloud technology has set the ground for an era of task offloading for mobile devices and we are now seeing the deployment of applications that make more extensive use of Cloud processing as a means of augmenting the capabilities of mobiles. Mobile Cloud Computing is the term used to describe the convergence of these technologies towards applications and mechanisms that offload tasks from mobile devices to the Cloud. In order for mobile devices to access Cloud resources and successfully offload tasks there, a solution for constant and reliable connectivity is required. The proliferation of wireless technology ensures that networks are available almost everywhere in an urban environment and mobile devices can stay connected to a network at all times. However, user mobility is often the cause of intermittent connectivity that affects the performance of applications and ultimately degrades the user experience. 5th Generation Networks are introducing mechanisms that enable constant and reliable connectivity through seamless handovers between networks and provide the foundation for a tighter coupling between Cloud resources and mobiles. This convergence of technologies creates new challenges in the areas of traffic management and QoS provisioning. The constant connectivity to and reliance of mobile devices on Cloud resources have the potential of creating large traffic flows between networks. Furthermore, depending on the type of application generating the traffic flow, very strict QoS may be required from the networks as suboptimal performance may severely degrade an application’s functionality. In this thesis, I propose a new service delivery framework, centred on the convergence of Mobile Cloud Computing and 5G networks for the purpose of optimising service delivery in a mobile environment. The framework is used as a guideline for identifying different aspects of service delivery in a mobile environment and for providing a path for future research in this field. The focus of the thesis is placed on the service delivery mechanisms that are responsible for optimising the QoS and managing network traffic. I present a solution for managing traffic through dynamic service localisation according to user mobility and device connectivity. I implement a prototype of the solution in a virtualised environment as a proof of concept and demonstrate the functionality and results gathered from experimentation. Finally, I present a new approach to modelling network performance by taking into account user mobility. The model considers the overall performance of a persistent connection as the mobile node switches between different networks. Results from the model can be used to determine which networks will negatively affect application performance and what impact they will have for the duration of the user's movement. The proposed model is evaluated using an analytical approac

Situation-aware Edge Computing

Future wireless networks must cope with an increasing amount of data that needs to be transmitted to or from mobile devices. Furthermore, novel applications, e.g., augmented reality games or autonomous driving, require low latency and high bandwidth at the same time. To address these challenges, the paradigm of edge computing has been proposed. It brings computing closer to the users and takes advantage of the capabilities of telecommunication infrastructures, e.g., cellular base stations or wireless access points, but also of end user devices such as smartphones, wearables, and embedded systems. However, edge computing introduces its own challenges, e.g., economic and business-related questions or device mobility. Being aware of the current situation, i.e., the domain-specific interpretation of environmental information, makes it possible to develop approaches targeting these challenges. In this thesis, the novel concept of situation-aware edge computing is presented. It is divided into three areas: situation-aware infrastructure edge computing, situation-aware device edge computing, and situation-aware embedded edge computing. Therefore, the concepts of situation and situation-awareness are introduced. Furthermore, challenges are identified for each area, and corresponding solutions are presented. In the area of situation-aware infrastructure edge computing, economic and business-related challenges are addressed, since companies offering services and infrastructure edge computing facilities have to find agreements regarding the prices for allowing others to use them. In the area of situation-aware device edge computing, the main challenge is to find suitable nodes that can execute a service and to predict a node’s connection in the near future. Finally, to enable situation-aware embedded edge computing, two novel programming and data analysis approaches are presented that allow programmers to develop situation-aware applications. To show the feasibility, applicability, and importance of situation-aware edge computing, two case studies are presented. The first case study shows how situation-aware edge computing can provide services for emergency response applications, while the second case study presents an approach where network transitions can be implemented in a situation-aware manner

Edge Computing Platforms and Protocols

Cloud computing has created a radical shift in expanding the reach of application usage and has emerged as a de-facto method to provide low-cost and highly scalable computing services to its users. Existing cloud infrastructure is a composition of large-scale networks of datacenters spread across the globe. These datacenters are carefully installed in isolated locations and are heavily managed by cloud providers to ensure reliable performance to its users. In recent years, novel applications, such as Internet-of-Things, augmented-reality, autonomous vehicles etc., have proliferated the Internet. Majority of such applications are known to be time-critical and enforce strict computational delay requirements for acceptable performance. Traditional cloud offloading techniques are inefficient for handling such applications due to the incorporation of additional network delay encountered while uploading pre-requisite data to distant datacenters. Furthermore, as computations involving such applications often rely on sensor data from multiple sources, simultaneous data upload to the cloud also results in significant congestion in the network. Edge computing is a new cloud paradigm which aims to bring existing cloud services and utilities near end users. Also termed edge clouds, the central objective behind this upcoming cloud platform is to reduce the network load on the cloud by utilizing compute resources in the vicinity of users and IoT sensors. Dense geographical deployment of edge clouds in an area not only allows for optimal operation of delay-sensitive applications but also provides support for mobility, context awareness and data aggregation in computations. However, the added functionality of edge clouds comes at the cost of incompatibility with existing cloud infrastructure. For example, while data center servers are closely monitored by the cloud providers to ensure reliability and security, edge servers aim to operate in unmanaged publicly-shared environments. Moreover, several edge cloud approaches aim to incorporate crowdsourced compute resources, such as smartphones, desktops, tablets etc., near the location of end users to support stringent latency demands. The resulting infrastructure is an amalgamation of heterogeneous, resource-constrained and unreliable compute-capable devices that aims to replicate cloud-like performance. This thesis provides a comprehensive collection of novel protocols and platforms for integrating edge computing in the existing cloud infrastructure. At its foundation lies an all-inclusive edge cloud architecture which allows for unification of several co-existing edge cloud approaches in a single logically classified platform. This thesis further addresses several open problems for three core categories of edge computing: hardware, infrastructure and platform. For hardware, this thesis contributes a deployment framework which enables interested cloud providers to effectively identify optimal locations for deploying edge servers in any geographical region. For infrastructure, the thesis proposes several protocols and techniques for efficient task allocation, data management and network utilization in edge clouds with the end-objective of maximizing the operability of the platform as a whole. Finally, the thesis presents a virtualization-dependent platform for application owners to transparently utilize the underlying distributed infrastructure of edge clouds, in conjunction with other co-existing cloud environments, without much management overhead.Pilvilaskenta on aikaansaanut suuren muutoksen sovellusten toiminta-alueessa ja on sen myötä muodostunut lähes oletusarvoiseksi tavaksi toteuttaa edullisia ja skaalautuvia laskentapalveluita käyttäjille. Olemassaoleva pilvi-infrastruktuuri on kokoelma suuren mittakaavan datakeskuksia ympäri maailman. Datakeskukset sijaitsevat maantieteellisesti tarkkaan valituissa paikoissa, joista pilvioperaattorit pystyvät takaamaan hyvän suorituskyvyn käyttäjilleen. Viime vuosina yleistyneet uudet sovellusalat, kuten esineiden Internet (IoT), lisätty todellisuus (AR), itseohjautuvat autot, jne., ovat yleistyneet Internetissä. Valtaosa edellä mainituista sovellusaloista on aikakriittisiä, ja ne asettavat laskennalle tiukan viivemarginaalin, jonka toteutuminen on edellytys sovelluksen hyväksyttävälle suorituskyvylle. Perinteiset menetelmät delegoida laskentaa pilvipalveluihin ovat kelvottomia aikakriittisissä sovelluksissa, sillä laskentaan liittyvän oheisdatan siirtämisestä johtuva verkkoviive on liian suuri. Useat edellä mainituista uusista sovellusaloista hyödyntävät sensoridataa, jota kerätään useista eri lähteistä. Samanaikaiset datayhteydet puolestaan aiheuttavat merkittävää ruuhkaa verkossa. Reunalaskenta on uusi pilviparadigma, jonka tavoitteena on tuoda nykyiset palvelut ja resurssit lähemmäksi loppukäyttäjää. Myös reunapilvenä tunnetun paradigman keskeinen tavoite on vähentää pilveen kohdistuvaa verkkoliikennettä suorittamalla sovelluksen vaatima laskenta resursseilla, jotka sijaitsevat lähempänä loppukäyttäjää. Reunapilvien tiheä maantieteellinen sijoittelu ei ainoastaan auta minimoimaan tiedonsiirtoviivettä aikakriittisiä sovelluksia varten, vaan tukee myös sovellusten mobiliteettia, kontekstitietoisuutta ja datan aggregointia laskentaa varten. Edellä mainitut reunapilven tarjoamat uudet mahdollisuudet eivät kuitenkaan ole yhteensopivia nykyisten pilvi-infrastruktuurien kanssa. Datakeskukset toimivat tarkoin valvotuissa ympäristöissä palvelun takaamiseksi, kun taas reunapilvien toiminta-alue on hallinnoimaton ja julkinen. Useat esitykset reunapilven toteutukseen liittyen hyödyntävät myös käyttäjien laitteiden potentiaalista laskentakapasiteettia, jota tänä päivänä löytyy runsaasti mm. älypuhelimista, kannettavista tietokoneista, tableteista. Reunapilven infrastruktuuri on täten haastava yhdistelmä heterogeenisiä, resurssirajoitettuja, epäluotettavia, mutta laskentakykyisiä laitteita, jotka yhdessä pyrkivät suorittamaan pilvilaskentaa. Tämä väitöstutkimus tarjoaa kokoelman uudentyyppisiä protokollia ja alustoja reunalaskennan integroimiseksi osaksi nykyistä pilvi-infrastruktuuria. Tutkimuksen pohjana on kokonaisvaltainen reunapilviarkkitehtuuri, joka pyrkii yhdistämään useita rinnakkaisia arkkitehtuuriehdotuksia yhdeksi loogiseksi pilvialustaksi. Väitöstutkimus ottaa myös kantaa useisiin avoimiin ongelmiin reunalaskennan kolmella osa-alueella: resurssit, infrastruktuuri ja palvelualusta. Resursseihin liittyen tämä väitöstutkimus tarjoaa käyttöönottokehyksen, jonka avulla palveluntarjoajat voivat tehokkaasti selvittää reunapalvelinten optimaaliset maantieteelliset sijoituskohteet. Infrastruktuurin osalta tämä väitöstutkimus esittelee reunapilvessä tapahtuvaa tehokasta tehtävien allokointia, datan hallinnointia ja verkon hyödyntämistä varten useita protokollia ja tekniikoita, joiden yhteinen tavoite on maksimoida alustan toiminnallisuus kokonaisuutena. Tämän väitöstutkimuksen lopussa kuvataan virtualisointiin pohjautuva alusta, jonka avulla käyttäjä voi läpinäkyvästi hyödyntää ympäröivää reunapilveä perinteisten pilvi-infrastruktuurien rinnalla ilman suurta hallinnollista kuormaa