Multi-access Edge Computing (MEC) has enabled low-latency computation offloading for provisioning... more Multi-access Edge Computing (MEC) has enabled low-latency computation offloading for provisioning latency-sensitive 5G services that may also require stringent reliability. Given the growing user demands incurring communication bottleneck in the access network, Unmanned Aerial Vehicles (UAVs) have been proposed to provide edge computation capability, through mounting them by cloudlets, hence, harnessing their various advantages such as flexibility, low-cost, and line of sight communication. However, the introduction of UAV-mounted cloudlets necessitates a novel study of the provisioned reliability while accounting for the high failure rate of UAV-mounted cloudlets, that can be caused by various factors. In this paper, we study the problem of reliability-aware computation offloading in a UAV-enabled MEC system. We aim at maximizing the number of served offloading requests, by optimizing the UAVs' positions, users' task partitioning and assignment, as well as the allocation of radio and computational resources. We formulate the problem as a non-convex mixed-integer program, and due to its complexity, we transform it into an approximate convex program and provide a low-complexity iterative algorithm based on the Successive Convex Approximation (SCA) method. Through numerical analysis, we demonstrate the efficiency of our solution, and study the achieved performance gains for various latency and reliability requirements corresponding to different use cases in 5G networks.
The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking ... more The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking dependencies on oil, as well as tapping into cleaner sources of energies and the remarkable initiatives taken by many countries are nurturing the enormous potential of Electric Vehicles (EV) of being our principal mode of transportation. EVs acceptance, however, is hindered by several challenges, among them is their shorter driving range, slower charging rate, and the lack of ubiquitous availability of charging locations, collectively contributing to higher anxieties for EVs drivers. Meanwhile, the expected immense EV load onto the power distribution sector may compromise the power quality. In this paper, we present a two stage solution to provision and dimension a DC fast charging network that minimizes the deployment cost while ensuring a certain quality of experience for charging (e.g., acceptable waiting time, shorter travel distance to charge, etc.). Further, we pay particular attention to maintain the voltage stability by adding a minimum number of voltage stabilizers upon the need to the power distribution network. We propose, evaluate and compare two CS (charging station) network expansion models to determine a cost effective and adaptive CSs provisioning solution that can efficiently expand the CS network to accommodate future charging demands. Finally, a custom built PYTHON-based discrete event simulator is developed to test our outcomes.
The sharing of computing and networking resources in the cloud is challenged by several obstacles... more The sharing of computing and networking resources in the cloud is challenged by several obstacles, such as providing bandwidth guarantees for a predictable performance of the hosted applications, as well as maintaining the availability of their services following outages. Therefore, the wide scale adoption of this emerging computing paradigm remains highly dependent on overcoming these challenges. In fact, a lack of bandwidth guarantees extends the completion time for jobs, thus increasing expenses for clients paying for their time of use. In addition, outages in data centers may result in severe revenue losses for both, the cloud operators and their clients alike. To overcome these challenges, cloud operators should be empowered with a strategic design plan that is able to guarantee resilient and predictable performance for hosted applications. Such a plan consists of provisioning additional backup resources (e.g.virtual machines, bandwidth) while ensuring efficient network bandwidth utilization. In this work, we study the design of various facets of such a plan. Namely, we exploit several bandwidth sharing opportunities in multi-tenant cloud networks while offering resilient and bandwidth guaranteed services. In contrast to previous works which target cloud clients satisfaction, we focus on optimizing network bandwidth utilization in order to increase the cloud operators revenues while maintaining such bandwidth allocation transparent to the clients. Through several motivational examples, and numerical studies, we highlight the sharing opportunities and show that they are able to increase cloud operators revenues by an average of 21.4% while providing up to 50% of bandwidth gain in the network.
Modern 5G services with stringent reliability and latency requirements such as smart healthcare a... more Modern 5G services with stringent reliability and latency requirements such as smart healthcare and industrial automation have become possible through the advancement of Multi-access Edge Computing (MEC). However, the rigidity of ground MEC and its susceptibility to infrastructure failure would prevent satisfying the resiliency and strict requirements of those services. Unmanned Aerial Vehicles (UAVs) have been proposed for providing flexible edge computing capability through UAV-mounted cloudlets, harnessing their advantages such as mobility, low-cost, and line-of-sight communication. However, UAV-mounted cloudlets may have failure rates that would impact mission-critical applications, necessitating a novel study for the provisioned reliability considering UAV node reliability and task redundancy. In this paper, we investigate the novel problem of UAV-aided ultra-reliable low-latency computation offloading which would enable future IoT services with strict requirements. We aim at maximizing the rate of served requests, by optimizing the UAVs’ positions, the offloading decisions, and the allocated resources while respecting the stringent latency and reliability requirements. To do so, the problem is divided into two phases, the first being a planning problem to optimize the placement of UAVs and the second an operational problem to make optimized offloading and resource allocation decisions with constrained UAVs’ energy. We formulate both problems associated with each phase as non-convex mixed-integer programs, and due to their non-convexity, we propose a two-stage approximate algorithm where the two problems are transformed into approximate convex programs. Further, we approach the problem considering the task partitioning model which will be prevalent in 5G networks. Through numerical analysis, we demonstrate the efficiency of our solution considering various scenarios, and compare it to other baseline approaches.
IEEE Transactions on Vehicular Technology, Jul 1, 2020
The concept of smart city strives for greener technology to reduce carbon emission to ameliorate ... more The concept of smart city strives for greener technology to reduce carbon emission to ameliorate the global warming. Following this footprint, the transportation sector is experiencing a paradigm shift and the transition to electric vehicles (EVs) has prodigious plausibility in reducing carbon emission. However, the anticipated EV penetration is hindered by several challenges, among them are their shorter driving range, slower charging rate and the lack of ubiquitous availability of charging locations, which collectively contribute to range anxieties for EVs' drivers. Meanwhile, the expected immense EV load onto the power distribution network may degrade the voltage stability. To reduce the range anxiety, we present a two-stage solution to provision and dimension a DC fast charging station (CS) network for the anticipated energy demand and that minimizes the deployment cost while ensuring a certain quality of experience for charging e.g., acceptable waiting time and shorter travel distance to charge. This solution also maintains the voltage stability by considering the distribution grid capacity, determining transformers’ rating to support peak demand of EV charging and adding a minimum number of voltage regulators based on the impact over the power distribution network. We propose, evaluate and compare two CS network expansion models to determine a cost-effective and adaptive CSs provisioning solution that can efficiently expand the CS network to accommodate future EV charging and conventional load demands. We also propose two heuristic methods and compare our solution with them. Finally, a custom built Python-based discrete event simulator is developed to test our outcomes.
2016 28th International Teletraffic Congress (ITC 28), 2016
The sharing of computing and networking resources in the cloud is challenged by several obstacles... more The sharing of computing and networking resources in the cloud is challenged by several obstacles, such as providing bandwidth guarantees for a predictable performance of the hosted applications, as well as maintaining the availability of their services following outages. Therefore, the wide scale adoption of this emerging computing paradigm remains highly dependent on overcoming these challenges. In fact, a lack of bandwidth guarantees extends the completion time for jobs, thus increasing expenses for clients paying for their time of use. In addition, outages in data centers may result in severe revenue losses for both, the cloud operators and their clients alike. To overcome these challenges, cloud operators should be empowered with a strategic design plan that is able to guarantee resilient and predictable performance for hosted applications. Such a plan consists of provisioning additional backup resources (e.g.virtual machines, bandwidth) while ensuring efficient network bandwidth utilization. In this work, we study the design of various facets of such a plan. Namely, we exploit several bandwidth sharing opportunities in multi-tenant cloud networks while offering resilient and bandwidth guaranteed services. In contrast to previous works which target cloud clients satisfaction, we focus on optimizing network bandwidth utilization in order to increase the cloud operators revenues while maintaining such bandwidth allocation transparent to the clients. Through several motivational examples, and numerical studies, we highlight the sharing opportunities and show that they are able to increase cloud operators revenues by an average of 21.4% while providing up to 50% of bandwidth gain in the network.
2016 12th International Conference on the Design of Reliable Communication Networks (DRCN), 2016
In cloud data centers, where hosted applications share the underlying network resources, network-... more In cloud data centers, where hosted applications share the underlying network resources, network-bandwidth guarantees have been shown to improve predictability of application performance and cost. However, recent empirical studies have also shown that often data center devices and links are not all that reliable and that failures may cause service outages, rendering significant revenue loss for the affected tenants, as well as the cloud operator. Accordingly, cloud operators are pressed to offer both reliable and predictable performance for the hosted applications. While much work has been done on solving both problems separately, this paper seeks to develop a joint framework by which cloud operators can offer both performance and availability guarantees for the hosted tenants. In particular, this paper considers a simple model to abstract the bandwidth guarantees requirement for the tenant and presents a protection plan design which consists of backup virtual machines placement and bandwidth provisioning to optimize the internal data center traffic. We show through solid motivational examples that finding the optimal protection plan design is highly perplexing, and encompasses several constituent challenges. Owing to its complexity, we decompose it into two subproblems, and solve them separately. First, we invoke a placement subproblem of the minimum number of backup VMs and then we attempt to find the most efficient correspondence between backup and primary VMs (i.e., protection plan) which minimizes the bandwidth redundancy. Our numerical evaluation shows that our two-step method is both scalable and accurate; further, it performs much better than a baseline method where placement of backup VMs is done at random.
IEEE Transactions on Network and Service Management, 2021
Cognitive network management is becoming quintessential to realize autonomic networking. However,... more Cognitive network management is becoming quintessential to realize autonomic networking. However, the wide spread adoption of the Internet of Things (IoT) devices, increases the risk of cyber attacks. Adversaries can exploit vulnerabilities in IoT devices, which can be harnessed to launch massive Distributed Denial of Service (DDoS) attacks. Therefore, intelligent security mechanisms are needed to harden network security against these threats. In this paper, we propose Chronos, a novel time-based anomaly detection system. The anomaly detector, primarily an Autoencoder, leverages time-based features over multiple time windows to efficiently detect anomalous DDoS traffic. We develop a threshold selection heuristic that maximizes the F1-score across various DDoS attacks. Further, we compare the performance of Chronos against state-of-the-art approaches. We show that Chronos marginally outperforms another timebased system using a less complex anomaly detection pipeline, while out classi...
The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking ... more The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking dependencies on oil, as well as tapping into cleaner sources of energies and the remarkable initiatives taken by many countries are nurturing the enormous potential of Electric Vehicles (EV) of being our principal mode of transportation. EVs acceptance, however, is hindered by several challenges, among them is their shorter driving range, slower charging rate, and the lack of ubiquitous availability of charging locations, collectively contributing to higher anxieties for EVs drivers. Meanwhile, the expected immense EV load onto the power distribution sector may compromise the power quality. In this paper, we present a two stage solution to provision and dimension a DC fast charging network that minimizes the deployment cost while ensuring a certain quality of experience for charging (e.g., acceptable waiting time, shorter travel distance to charge, etc.). Further, we pay particular atten...
Multi-access Edge Computing (MEC) has enabled low-latency computation offloading for provisioning... more Multi-access Edge Computing (MEC) has enabled low-latency computation offloading for provisioning latency-sensitive 5G services that may also require stringent reliability. Given the growing user demands incurring communication bottleneck in the access network, Unmanned Aerial Vehicles (UAVs) have been proposed to provide edge computation capability, through mounting them by cloudlets, hence, harnessing their various advantages such as flexibility, low-cost, and line of sight communication. However, the introduction of UAV-mounted cloudlets necessitates a novel study of the provisioned reliability while accounting for the high failure rate of UAV-mounted cloudlets, that can be caused by various factors. In this paper, we study the problem of reliability-aware computation offloading in a UAV-enabled MEC system. We aim at maximizing the number of served offloading requests, by optimizing the UAVs' positions, users' task partitioning and assignment, as well as the allocation of radio and computational resources. We formulate the problem as a non-convex mixed-integer program, and due to its complexity, we transform it into an approximate convex program and provide a low-complexity iterative algorithm based on the Successive Convex Approximation (SCA) method. Through numerical analysis, we demonstrate the efficiency of our solution, and study the achieved performance gains for various latency and reliability requirements corresponding to different use cases in 5G networks.
The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking ... more The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking dependencies on oil, as well as tapping into cleaner sources of energies and the remarkable initiatives taken by many countries are nurturing the enormous potential of Electric Vehicles (EV) of being our principal mode of transportation. EVs acceptance, however, is hindered by several challenges, among them is their shorter driving range, slower charging rate, and the lack of ubiquitous availability of charging locations, collectively contributing to higher anxieties for EVs drivers. Meanwhile, the expected immense EV load onto the power distribution sector may compromise the power quality. In this paper, we present a two stage solution to provision and dimension a DC fast charging network that minimizes the deployment cost while ensuring a certain quality of experience for charging (e.g., acceptable waiting time, shorter travel distance to charge, etc.). Further, we pay particular attention to maintain the voltage stability by adding a minimum number of voltage stabilizers upon the need to the power distribution network. We propose, evaluate and compare two CS (charging station) network expansion models to determine a cost effective and adaptive CSs provisioning solution that can efficiently expand the CS network to accommodate future charging demands. Finally, a custom built PYTHON-based discrete event simulator is developed to test our outcomes.
The sharing of computing and networking resources in the cloud is challenged by several obstacles... more The sharing of computing and networking resources in the cloud is challenged by several obstacles, such as providing bandwidth guarantees for a predictable performance of the hosted applications, as well as maintaining the availability of their services following outages. Therefore, the wide scale adoption of this emerging computing paradigm remains highly dependent on overcoming these challenges. In fact, a lack of bandwidth guarantees extends the completion time for jobs, thus increasing expenses for clients paying for their time of use. In addition, outages in data centers may result in severe revenue losses for both, the cloud operators and their clients alike. To overcome these challenges, cloud operators should be empowered with a strategic design plan that is able to guarantee resilient and predictable performance for hosted applications. Such a plan consists of provisioning additional backup resources (e.g.virtual machines, bandwidth) while ensuring efficient network bandwidth utilization. In this work, we study the design of various facets of such a plan. Namely, we exploit several bandwidth sharing opportunities in multi-tenant cloud networks while offering resilient and bandwidth guaranteed services. In contrast to previous works which target cloud clients satisfaction, we focus on optimizing network bandwidth utilization in order to increase the cloud operators revenues while maintaining such bandwidth allocation transparent to the clients. Through several motivational examples, and numerical studies, we highlight the sharing opportunities and show that they are able to increase cloud operators revenues by an average of 21.4% while providing up to 50% of bandwidth gain in the network.
Modern 5G services with stringent reliability and latency requirements such as smart healthcare a... more Modern 5G services with stringent reliability and latency requirements such as smart healthcare and industrial automation have become possible through the advancement of Multi-access Edge Computing (MEC). However, the rigidity of ground MEC and its susceptibility to infrastructure failure would prevent satisfying the resiliency and strict requirements of those services. Unmanned Aerial Vehicles (UAVs) have been proposed for providing flexible edge computing capability through UAV-mounted cloudlets, harnessing their advantages such as mobility, low-cost, and line-of-sight communication. However, UAV-mounted cloudlets may have failure rates that would impact mission-critical applications, necessitating a novel study for the provisioned reliability considering UAV node reliability and task redundancy. In this paper, we investigate the novel problem of UAV-aided ultra-reliable low-latency computation offloading which would enable future IoT services with strict requirements. We aim at maximizing the rate of served requests, by optimizing the UAVs’ positions, the offloading decisions, and the allocated resources while respecting the stringent latency and reliability requirements. To do so, the problem is divided into two phases, the first being a planning problem to optimize the placement of UAVs and the second an operational problem to make optimized offloading and resource allocation decisions with constrained UAVs’ energy. We formulate both problems associated with each phase as non-convex mixed-integer programs, and due to their non-convexity, we propose a two-stage approximate algorithm where the two problems are transformed into approximate convex programs. Further, we approach the problem considering the task partitioning model which will be prevalent in 5G networks. Through numerical analysis, we demonstrate the efficiency of our solution considering various scenarios, and compare it to other baseline approaches.
IEEE Transactions on Vehicular Technology, Jul 1, 2020
The concept of smart city strives for greener technology to reduce carbon emission to ameliorate ... more The concept of smart city strives for greener technology to reduce carbon emission to ameliorate the global warming. Following this footprint, the transportation sector is experiencing a paradigm shift and the transition to electric vehicles (EVs) has prodigious plausibility in reducing carbon emission. However, the anticipated EV penetration is hindered by several challenges, among them are their shorter driving range, slower charging rate and the lack of ubiquitous availability of charging locations, which collectively contribute to range anxieties for EVs' drivers. Meanwhile, the expected immense EV load onto the power distribution network may degrade the voltage stability. To reduce the range anxiety, we present a two-stage solution to provision and dimension a DC fast charging station (CS) network for the anticipated energy demand and that minimizes the deployment cost while ensuring a certain quality of experience for charging e.g., acceptable waiting time and shorter travel distance to charge. This solution also maintains the voltage stability by considering the distribution grid capacity, determining transformers’ rating to support peak demand of EV charging and adding a minimum number of voltage regulators based on the impact over the power distribution network. We propose, evaluate and compare two CS network expansion models to determine a cost-effective and adaptive CSs provisioning solution that can efficiently expand the CS network to accommodate future EV charging and conventional load demands. We also propose two heuristic methods and compare our solution with them. Finally, a custom built Python-based discrete event simulator is developed to test our outcomes.
2016 28th International Teletraffic Congress (ITC 28), 2016
The sharing of computing and networking resources in the cloud is challenged by several obstacles... more The sharing of computing and networking resources in the cloud is challenged by several obstacles, such as providing bandwidth guarantees for a predictable performance of the hosted applications, as well as maintaining the availability of their services following outages. Therefore, the wide scale adoption of this emerging computing paradigm remains highly dependent on overcoming these challenges. In fact, a lack of bandwidth guarantees extends the completion time for jobs, thus increasing expenses for clients paying for their time of use. In addition, outages in data centers may result in severe revenue losses for both, the cloud operators and their clients alike. To overcome these challenges, cloud operators should be empowered with a strategic design plan that is able to guarantee resilient and predictable performance for hosted applications. Such a plan consists of provisioning additional backup resources (e.g.virtual machines, bandwidth) while ensuring efficient network bandwidth utilization. In this work, we study the design of various facets of such a plan. Namely, we exploit several bandwidth sharing opportunities in multi-tenant cloud networks while offering resilient and bandwidth guaranteed services. In contrast to previous works which target cloud clients satisfaction, we focus on optimizing network bandwidth utilization in order to increase the cloud operators revenues while maintaining such bandwidth allocation transparent to the clients. Through several motivational examples, and numerical studies, we highlight the sharing opportunities and show that they are able to increase cloud operators revenues by an average of 21.4% while providing up to 50% of bandwidth gain in the network.
2016 12th International Conference on the Design of Reliable Communication Networks (DRCN), 2016
In cloud data centers, where hosted applications share the underlying network resources, network-... more In cloud data centers, where hosted applications share the underlying network resources, network-bandwidth guarantees have been shown to improve predictability of application performance and cost. However, recent empirical studies have also shown that often data center devices and links are not all that reliable and that failures may cause service outages, rendering significant revenue loss for the affected tenants, as well as the cloud operator. Accordingly, cloud operators are pressed to offer both reliable and predictable performance for the hosted applications. While much work has been done on solving both problems separately, this paper seeks to develop a joint framework by which cloud operators can offer both performance and availability guarantees for the hosted tenants. In particular, this paper considers a simple model to abstract the bandwidth guarantees requirement for the tenant and presents a protection plan design which consists of backup virtual machines placement and bandwidth provisioning to optimize the internal data center traffic. We show through solid motivational examples that finding the optimal protection plan design is highly perplexing, and encompasses several constituent challenges. Owing to its complexity, we decompose it into two subproblems, and solve them separately. First, we invoke a placement subproblem of the minimum number of backup VMs and then we attempt to find the most efficient correspondence between backup and primary VMs (i.e., protection plan) which minimizes the bandwidth redundancy. Our numerical evaluation shows that our two-step method is both scalable and accurate; further, it performs much better than a baseline method where placement of backup VMs is done at random.
IEEE Transactions on Network and Service Management, 2021
Cognitive network management is becoming quintessential to realize autonomic networking. However,... more Cognitive network management is becoming quintessential to realize autonomic networking. However, the wide spread adoption of the Internet of Things (IoT) devices, increases the risk of cyber attacks. Adversaries can exploit vulnerabilities in IoT devices, which can be harnessed to launch massive Distributed Denial of Service (DDoS) attacks. Therefore, intelligent security mechanisms are needed to harden network security against these threats. In this paper, we propose Chronos, a novel time-based anomaly detection system. The anomaly detector, primarily an Autoencoder, leverages time-based features over multiple time windows to efficiently detect anomalous DDoS traffic. We develop a threshold selection heuristic that maximizes the F1-score across various DDoS attacks. Further, we compare the performance of Chronos against state-of-the-art approaches. We show that Chronos marginally outperforms another timebased system using a less complex anomaly detection pipeline, while out classi...
The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking ... more The rising awareness for maintaining a clean environment, reducing pollutant emissions, breaking dependencies on oil, as well as tapping into cleaner sources of energies and the remarkable initiatives taken by many countries are nurturing the enormous potential of Electric Vehicles (EV) of being our principal mode of transportation. EVs acceptance, however, is hindered by several challenges, among them is their shorter driving range, slower charging rate, and the lack of ubiquitous availability of charging locations, collectively contributing to higher anxieties for EVs drivers. Meanwhile, the expected immense EV load onto the power distribution sector may compromise the power quality. In this paper, we present a two stage solution to provision and dimension a DC fast charging network that minimizes the deployment cost while ensuring a certain quality of experience for charging (e.g., acceptable waiting time, shorter travel distance to charge, etc.). Further, we pay particular atten...
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