2019
[5]
R. Singh, S. Armour, A. Khan, M. Sooriyabandara, G. Oikonomou, "The Advantage of Computation Offloading in Multi-Access Edge Computing", in Proc. IEEE FMEC, 2019 (accepted, to appear)
@inproceedings{Singh-2019-FMEC, title = {The Advantage of Computation Offloading in Multi-Access Edge Computing}, author = {Raghubir Singh and Simon Armour and Aftab Khan and Mahesh Sooriyabandara and George Oikonomou}, year = {2019}, month = jun, booktitle = {Proc. IEEE FMEC}, note = {accepted, to appear}, oa-url = {https://research-information.bristol.ac.uk/en/publications/the-advantage-of-computation-offloading-in-multiaccess-edge-computing(c528b331-9ae0-436f-961e-9976ed62bba9).html }, abstract = {Computation offloading plays a critical role inreducing task completion time for mobile devices. The advantagesof computation offloading to cloud resources in Mobile CloudComputing have been widely considered. In this paper, we haveinvestigated different scenarios for offloading to less distantMulti-Access Edge Computing (MEC) servers for multiple userswith a range of mobile devices and computational tasks. Wepresent detailed simulation data for how offloading can bebeneficial in a MEC network with varying quantitative mobileuser demand, heterogeneity in mobile device on-board and MECprocessor speeds, computational task complexity, communicationspeeds, link access delays and mobile device user numbers.Unlike previous work where simulations considered only limitedcommunication speeds for offloading, we have extended the rangeof link speeds and included two types of communication delay.We find that more computationally complex applications areoffloaded preferentially (especially with the higher server:mobiledevice processor speed ratios) while low link speeds and anydelays caused by network delays or excessive user numbersdegrade any advantages in reduced task completion times offeredby offloading. Additionally, significant savings in energy usage bymobile devices are guaranteed except at very low link speeds.}, }
Computation offloading plays a critical role inreducing task completion time for mobile devices. The advantagesof computation offloading to cloud resources in Mobile CloudComputing have been widely considered. In this paper, we haveinvestigated different scenarios for offloading to less distantMulti-Access Edge Computing (MEC) servers for multiple userswith a range of mobile devices and computational tasks. Wepresent detailed simulation data for how offloading can bebeneficial in a MEC network with varying quantitative mobileuser demand, heterogeneity in mobile device on-board and MECprocessor speeds, computational task complexity, communicationspeeds, link access delays and mobile device user numbers.Unlike previous work where simulations considered only limitedcommunication speeds for offloading, we have extended the rangeof link speeds and included two types of communication delay.We find that more computationally complex applications areoffloaded preferentially (especially with the higher server:mobiledevice processor speed ratios) while low link speeds and anydelays caused by network delays or excessive user numbersdegrade any advantages in reduced task completion times offeredby offloading. Additionally, significant savings in energy usage bymobile devices are guaranteed except at very low link speeds.
[4]
M. Baddeley, U. Raza, M. Sooriyabandara, G. Oikonomou, R. Nejabati, D. Simeonidou, "Atomic-SDN: A Synchronous Flooding Framework for SDN Control of Low-Power Wireless", in Proc. ACM EWSN, 2019
@inproceedings{Baddeley-2019-EWSN, title = {Atomic-SDN: A Synchronous Flooding Framework for SDN Control of Low-Power Wireless}, author = {Michael Baddeley and Usman Raza and Mahesh Sooriyabandara and George Oikonomou and Reza Nejabati and Dimitra Simeonidou}, booktitle = {Proc. ACM EWSN}, publisher = {Association for Computing Machinery (ACM)}, year = {2019}, month = feb, oa-url = {https://research-information.bristol.ac.uk/en/publications/atomicsdn(35df9370-3ded-45dc-acc2-26bd36aad29b).html}, gsid = {15963983663240748841}, abstract = {We present Atomic-SDN, a highly flexible framework capable of dynamically scheduling synchronous flooding phases to accommodate multiple traffic patterns resulting from application-level requirements. Specifically, Atomic-SDN accommodates the complex and varying traffic generated in a Software Defined Networking (SDN) control solutions for low-power wireless networks, where the high-overhead and centralized nature of SDN causes considerable problems due to the constrained nature of the network. By utilizing the high-reliability and low-latency properties of synchronous flooding, our results show that Atomic-SDN is capable of providing minimal bounded latency guarantees for network-wide SDN operations. This reduces the time to perform SDN operations on all nodes by orders-of-magnitude, and allows core SDN concepts to be pushed to the very edge of IoT networks.}, }
We present Atomic-SDN, a highly flexible framework capable of dynamically scheduling synchronous flooding phases to accommodate multiple traffic patterns resulting from application-level requirements. Specifically, Atomic-SDN accommodates the complex and varying traffic generated in a Software Defined Networking (SDN) control solutions for low-power wireless networks, where the high-overhead and centralized nature of SDN causes considerable problems due to the constrained nature of the network. By utilizing the high-reliability and low-latency properties of synchronous flooding, our results show that Atomic-SDN is capable of providing minimal bounded latency guarantees for network-wide SDN operations. This reduces the time to perform SDN operations on all nodes by orders-of-magnitude, and allows core SDN concepts to be pushed to the very edge of IoT networks.
[3]
M. Baddeley, A. Stanoev, U. Raza, G. Oikonomou, R. Nejabati, D. Simeonidou, M. Sooriyabandara, "Atomic-SDN: A Synchronous Flooding Framework for SDN Control of Low-Power Wireless", IEEE Access, IEEE, 2019 (in press)
@article{Baddeley-2019-access, title = {Atomic-SDN: A Synchronous Flooding Framework for SDN Control of Low-Power Wireless}, author = {Michael Baddeley and Aleksandar Stanoev and Usman Raza and George Oikonomou and Reza Nejabati and Dimitra Simeonidou and Mahesh Sooriyabandara}, journal = {IEEE Access}, publisher = {Association for Computing Machinery (ACM)}, year = {2019}, publisher = {IEEE}, gsid = {17470899592040512837}, doi = {10.1109/ACCESS.2019.2920100}, oa-url = {http://dx.doi.org/10.1109/ACCESS.2019.2920100}, note = {in press}, abstract = {The adoption of Software Defined Networking (SDN) within traditional networks has provided operators the ability to manage diverse resources and easily reconfigure networks as requirements change. Recent research has extended this concept to IEEE 802.15.4 low-power wireless networks, which form a key component of the Internet of Things (IoT). However, the multiple traffic patterns necessary for SDN control makes it difficult to apply this approach to these highly challenging environments. This paper presents Atomic-SDN, a highly reliable and low-latency solution for SDN in low-power wireless. Atomic-SDN introduces a novel Synchronous Flooding (SF) architecture capable of dynamically configuring SF protocols to satisfy complex SDN control requirements, and draws from the authors' previous experiences in the IEEE EWSN Dependability Competition: where SF solutions have consistently outperformed other entries. Using this approach, Atomic-SDN presents considerable performance gains over other SDN implementations for low-power IoT networks. We evaluate Atomic-SDN through simulation and experimentation, and show how utilizing SF techniques provides latency and reliability guarantees to SDN control operations as the local mesh scales. We compare Atomic-SDN against other SDN implementations based on the IEEE 802.15.4 network stack, and establish that Atomic-SDN improves SDN control by orders-of-magnitude across latency, reliability, and energy-efficiency metrics.}, }
The adoption of Software Defined Networking (SDN) within traditional networks has provided operators the ability to manage diverse resources and easily reconfigure networks as requirements change. Recent research has extended this concept to IEEE 802.15.4 low-power wireless networks, which form a key component of the Internet of Things (IoT). However, the multiple traffic patterns necessary for SDN control makes it difficult to apply this approach to these highly challenging environments. This paper presents Atomic-SDN, a highly reliable and low-latency solution for SDN in low-power wireless. Atomic-SDN introduces a novel Synchronous Flooding (SF) architecture capable of dynamically configuring SF protocols to satisfy complex SDN control requirements, and draws from the authors' previous experiences in the IEEE EWSN Dependability Competition: where SF solutions have consistently outperformed other entries. Using this approach, Atomic-SDN presents considerable performance gains over other SDN implementations for low-power IoT networks. We evaluate Atomic-SDN through simulation and experimentation, and show how utilizing SF techniques provides latency and reliability guarantees to SDN control operations as the local mesh scales. We compare Atomic-SDN against other SDN implementations based on the IEEE 802.15.4 network stack, and establish that Atomic-SDN improves SDN control by orders-of-magnitude across latency, reliability, and energy-efficiency metrics.
2018
[2]
M. Baddeley, R. Nejabati, G. Oikonomou, M. Sooriyabandara, D. Simeonidou, "Evolving SDN for Low-Power IoT Networks", in Proc. NetSoft, 2018
@INPROCEEDINGS{Baddeley-2018-netsoft, title = {Evolving SDN for Low-Power IoT Networks}, author = {Michael Baddeley and Reza Nejabati and George Oikonomou and Mahesh Sooriyabandara and Dimitra Simeonidou}, booktitle = {Proc. NetSoft}, year = {2018}, oa-url = {https://research-information.bristol.ac.uk/en/publications/evolving-sdn-for-lowpower-iot-networks(f9eb201c-8800-45af-bab5-6b86d440e952).html}, doi = {10.1109/NETSOFT.2018.8460125}, gsid = {13759044828155681085}, abstract = {Software Defined Networking (SDN) offers a flexible and scalable architecture that abstracts decision making away from individual devices and provides a programmable network platform. Low-power wireless Internet of Things (IoT) networks, where multi-tenant and multi-application architectures require scalable and configurable solutions, are ideally placed to capitalize on this research. However, implementing a centralized SDN architecture within the constraints of a low-power wireless network faces considerable challenges. Not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper addresses the challenge of bringing high-overhead SDN architecture to IEEE 802.15.4 networks. We explore how the traditional view of SDN needs to evolve in order to overcome the constraints of low-power wireless networks, and discuss protocol and architectural optimizations necessary to reduce SDN control overhead - the main barrier to successful implementation. Additionally, we argue that interoperability with the existing protocol stack is necessary to provide a platform for controller discovery, and coexistence with legacy networks. We consequently introduce µSDN, a lightweight SDN framework for Contiki OS with both IPv6 and underlying routing protocol interoperability, as well as optimizing a number of elements within the SDN architecture to reduce control overhead to practical levels. We evaluate µSDN in terms of latency, energy, and packet delivery. Through this evaluation we show how the cost of SDN control overhead (both bootstrapping and management) can be reduced to a point where comparable performance and scalability is achieved against an IEEE 802.15.4-2012 RPL-based network. Additionally, we demonstrate µSDN through simulation: providing a use-case where the SDN configurability can be used to provide Quality of Service (QoS) for critical network flows experiencing interference, and we achieve considerable reductions in delay and jitter in comparison to a scenario without SDN.}, }
Software Defined Networking (SDN) offers a flexible and scalable architecture that abstracts decision making away from individual devices and provides a programmable network platform. Low-power wireless Internet of Things (IoT) networks, where multi-tenant and multi-application architectures require scalable and configurable solutions, are ideally placed to capitalize on this research. However, implementing a centralized SDN architecture within the constraints of a low-power wireless network faces considerable challenges. Not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper addresses the challenge of bringing high-overhead SDN architecture to IEEE 802.15.4 networks. We explore how the traditional view of SDN needs to evolve in order to overcome the constraints of low-power wireless networks, and discuss protocol and architectural optimizations necessary to reduce SDN control overhead - the main barrier to successful implementation. Additionally, we argue that interoperability with the existing protocol stack is necessary to provide a platform for controller discovery, and coexistence with legacy networks. We consequently introduce µSDN, a lightweight SDN framework for Contiki OS with both IPv6 and underlying routing protocol interoperability, as well as optimizing a number of elements within the SDN architecture to reduce control overhead to practical levels. We evaluate µSDN in terms of latency, energy, and packet delivery. Through this evaluation we show how the cost of SDN control overhead (both bootstrapping and management) can be reduced to a point where comparable performance and scalability is achieved against an IEEE 802.15.4-2012 RPL-based network. Additionally, we demonstrate µSDN through simulation: providing a use-case where the SDN configurability can be used to provide Quality of Service (QoS) for critical network flows experiencing interference, and we achieve considerable reductions in delay and jitter in comparison to a scenario without SDN.
2017
[1]
M. Baddeley, R. Nejabati, G. Oikonomou, S. Gormus, M. Sooriyabandara, D. Simeonidou, "Isolating SDN control traffic with layer-2 slicing in 6TiSCH industrial IoT networks", in Proc. IEEE NFV-SDN, pp. 247-251, 2017
@INPROCEEDINGS{Baddeley-2018-nfv-sdn, author = {Michael Baddeley and Reza Nejabati and George Oikonomou and Sedat Gormus and Mahesh Sooriyabandara and Dimitra Simeonidou}, booktitle = {Proc. IEEE NFV-SDN}, title = {Isolating SDN control traffic with layer-2 slicing in 6TiSCH industrial IoT networks}, year = {2017}, month = nov, pages = {247-251}, publisher = {IEEE}, doi = {10.1109/NFV-SDN.2017.8169876}, gsid = {3676551668416552782}, oa-url = {https://research-information.bristol.ac.uk/en/publications/isolating-sdn-control-traffic-with-layer2-slicing-in-6tisch-industrial-iot-networks(9873c63c-8204-4f73-8c80-68fa3eedd9e9).html}, abstract = {Recent standardization efforts in IEEE 802.15.4-2015 Time Scheduled Channel Hopping (TSCH) and the IETF 6TiSCH Working Group (WG), aim to provide deterministic communications and efficient allocation of resources across constrained Internet of Things (IoT) networks, particularly in Industrial IoT (IIoT) scenarios. Within 6TiSCH, Software Defined Networking (SDN) has been identified as means of providing centralized control in a number of key situations. However, implementing a centralized SDN architecture in a Low Power and Lossy Network (LLN) faces considerable challenges: not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper proposes using 6TiSCH tracks, a Layer-2 slicing mechanism for creating dedicated forwarding paths across TSCH networks, in order to isolate the SDN control overhead. Not only does this prevent control traffic from affecting the performance of other data flows, but the properties of 6TiSCH tracks allows deterministic, low-latency SDN controller communication. Using our own lightweight SDN implementation for Contiki OS, we firstly demonstrate the effect of SDN control traffic on application data flows across a 6TiSCH network. We then show that by slicing the network through the allocation of dedicated resources along a SDN control path, tracks provide an effective means of mitigating the cost of SDN control overhead in IEEE 802.15.4-2015 TSCH networks.}, }
Recent standardization efforts in IEEE 802.15.4-2015 Time Scheduled Channel Hopping (TSCH) and the IETF 6TiSCH Working Group (WG), aim to provide deterministic communications and efficient allocation of resources across constrained Internet of Things (IoT) networks, particularly in Industrial IoT (IIoT) scenarios. Within 6TiSCH, Software Defined Networking (SDN) has been identified as means of providing centralized control in a number of key situations. However, implementing a centralized SDN architecture in a Low Power and Lossy Network (LLN) faces considerable challenges: not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper proposes using 6TiSCH tracks, a Layer-2 slicing mechanism for creating dedicated forwarding paths across TSCH networks, in order to isolate the SDN control overhead. Not only does this prevent control traffic from affecting the performance of other data flows, but the properties of 6TiSCH tracks allows deterministic, low-latency SDN controller communication. Using our own lightweight SDN implementation for Contiki OS, we firstly demonstrate the effect of SDN control traffic on application data flows across a 6TiSCH network. We then show that by slicing the network through the allocation of dedicated resources along a SDN control path, tracks provide an effective means of mitigating the cost of SDN control overhead in IEEE 802.15.4-2015 TSCH networks.
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