Papers by Nashid Shahriar
IEEE Journal on Selected Areas in Communications, Jan 5, 2016
Middleboxes have become a vital part of modern networks by providing service functions such as co... more Middleboxes have become a vital part of modern networks by providing service functions such as content filtering, load balancing and optimization of network traffic. An ordered sequence of middleboxes composing a logical service is called service chain. Service Function Chaining (SFC) enables us to define these service chains. Recent optimization models of SFCs assume that the functionality of a middlebox is provided by a single software appliance, commonly known as Virtual Network Function (VNF). This assumption limits SFCs to the throughput of an individual VNF and resources of a physical machine hosting the VNF instance. Moreover, typical service providers offer VNFs with heterogeneous throughput and resource configurations. Thus, deploying a service chain with custom throughput can become a tedious process of stitching heterogeneous VNF instances. In this paper, we describe how we can overcome these limitations without worrying about underlying VNF configurations and resource constraints. This prospect is achieved by distributed deploying multiple VNF instances providing the functionality of a middlebox and modeling the optimal deployment of a service chain as a mixed integer programming problem. The proposed model optimizes host and bandwidth resources allocation, and determines the optimal placement of VNF instances, while balancing workload and routing traffic among these VNF instances. We show that this problem is NP-Hard and propose a heuristic solution called Kariz. Kariz utilizes a tuning parameter to control the trade-off between speed and accuracy of the solution. Finally, our solution is evaluated using simulations in data-center networks.
2021 17th International Conference on Network and Service Management (CNSM), 2021
5G transport networks will support dynamic services with diverse requirements through network sli... more 5G transport networks will support dynamic services with diverse requirements through network slicing. Elastic Optical Networks (EONs) facilitate transport network slicing by flexible spectrum allocation and tuning of transmission configurations such as modulation format and forward error correction. A major challenge in supporting dynamic services is the lack of a priori knowledge of future slice requests. In consequence, slice embedding can become sub-optimal over time, leading to spectrum fragmentation and skewed utilization. This in turn can block future slice requests, impacting operator revenue. Therefore, operators need to periodically re-optimize slice embedding for reducing fragmentation. In this paper, we address this problem of re-optimizing network slice embedding on EONs for minimizing fragmentation. The problem is solved in its splittable version, which significantly increases problem complexity, but offers more opportunities for a larger set of re-configuration actions. We employ simulated annealing for systematically exploring the large solution space. We also propose a greedy algorithm to address the practical constraint to limit the number of re-configuration steps taken to reach a defragmentated state. Our extensive simulations demonstrate that the greedy algorithm yields a solution very close to that obtained using simulated annealing while requiring orders of magnitude lesser number of re-configuration actions.
2010 24th IEEE International Conference on Advanced Information Networking and Applications Iterative Route Discovery in AODV
Abstract—Several protocols for ad hoc network try to reduce redundancy as an effective measure ag... more Abstract—Several protocols for ad hoc network try to reduce redundancy as an effective measure against broadcast problems. Though these protocols ensure good performance in a favorable environment, they perform poorly when node cooperation cannot be guaranteed due to intentional misbehavior or environmental hostility. As a result, the expected behavior of nodes to forward packets, which is the basic assumption of all broadcast approaches, cannot be achieved always. In this paper, we analyze the performance deterioration of these algorithms in hostile environment. As a remedy, we focus on the reverse direction and interestingly find that adding redundancy in a controlled manner can greatly compensate the performance loss due to node misbehavior. Here we propose a novel approach that tune the amount of redundancy so that reachability and routing load both remain at a satisfactory level. Comparing their relative performance we end up with the conclusion that though redundancy is undesi...
IEEE Journal on Selected Areas in Communications, 2021
Elastic Optical Networks (EONs) enable finer-grained resource allocation and tuning of transmissi... more Elastic Optical Networks (EONs) enable finer-grained resource allocation and tuning of transmission configurations for right-sized resource allocation. These features make EONs excellent choice for 5G transport networks supporting highly dynamic traffic with diverse Quality-of-Service (QoS) requirements. 5G network slices are expected to host applications with a dynamic nature (e.g., augmented/virtual reality broadcasting), which will result in slice resource requirement changing over time. The initial resource allocation to network slices has to be adapted to accommodate such changes without causing significant disruption to existing traffic and using minimal additional resources. In this paper, we address the problem of scaling bandwidth demand of network slices on an EON-enabled 5G transport network. In contrast to the state-of-the-art, we do not assume any specific technologies for minimizing disruption when accommodating the scaling request. Rather, we propose an Integer Linear...
Despite their tremendous success, centrally controlled cloud based solutions for social media net... more Despite their tremendous success, centrally controlled cloud based solutions for social media networking have inherent issues related to privacy and user control. Alternatively, a decentralized approach can be used, but ensuring content availability will be the major challenge. In this work, we propose a time based user grouping and content replication protocol that exploits the cyclic diurnal pattern in user uptime behaviour to ensure content persistence with minimal replication overhead. We also introduce the concept of β-availability, and propose a mechanism for ensuring the availability of at least β members within a replication group at any given time. Simulation results show that a 2-availability grouping policy delivers high content persistence without incurring significant network and storage overheads.
Ensuring content persistence with minimal replication overhead is a prerequisite for providing an... more Ensuring content persistence with minimal replication overhead is a prerequisite for providing any consistent service over a peer-to-peer (P2P) overlay. This paper introduces S-DATA, a bandwidth efficient protocol for achieving highly available P2P systems with minimal replication overhead. When considering a global P2P system, the cyclic behavior of peers situated at different time zones can be found complementary of one another. In S-DATA, peers with complementary diurnal availability patterns collaborate in small replication groups and host each other’s content in turn to ensure 24/7 availability. In this work we present a mathematical model for measuring time-based availability with (β−1) redundancy as a function of replication group size and peer uptime behavior. We also simulate the S-DATA protocol in the PeerSim simulator and compare its performance against a few other time-based replication protocols.
2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), 2017
Perceived as a key enabling technology for the future Internet, Network Virtualization (NV) allow... more Perceived as a key enabling technology for the future Internet, Network Virtualization (NV) allows an Infrastructure Provider (InP) to better utilize their Substrate Network (SN) by provisioning multiple Virtual Networks (VNs) from different Service Providers (SPs). A key challenge in NV is to efficiently map the VN requests from SPs on an SN, known as the Virtual Network Embedding (VNE) problem. VNE algorithms are typically online in nature. A VN embedding can become suboptimal over time due to the arrival and departure of other VNs as well as due to changes in SN such as failures. One way to mitigate the impact of such dynamism is to periodically reallocate resources for the existing VNs. VNE reallocation can increase an InP's revenue by decreasing bandwidth consumption and by increasing the possibility of accepting future VNs. In this paper, we study Reallocation of Virtual Network Embedding (ReViNE) problem to minimize the number of over utilized substrate links and total bandwidth cost on the SN. We propose an Integer Linear Programming formulation for the optimal solution (ReViNE-OPT) and a simulated annealing based heuristic (ReViNE-FAST) to solve larger problem instances. Simulation results show that on average our proposed heuristic performs within ∼19% of the optimal solution. Moreover, ReViNE-FAST generates more than 2.5× better solutions compared to the state-of-the-art simulated annealing based heuristic for VNE reallocation.
Proceedings of the 4th FlexNets Workshop on Flexible Networks Artificial Intelligence Supported Network Flexibility and Agility, 2021
The 5th Generation (5G) mobile networks support a wide range of services that impose diverse and ... more The 5th Generation (5G) mobile networks support a wide range of services that impose diverse and stringent QoS requirements. This will be further exacerbated with the evolution towards 6th Generation mobile networks. Inevitably, 5G and beyond mobile networks must provide stricter, differentiated QoS guarantees to meet the increasing demands of future applications, which cannot be satisfied with traditional human-in-the-loop service orchestration and network management approaches. In this paper, we lay out our vision for closed-loop service orchestration and network management of 5G and beyond mobile networks. We extend the MAPE (i.e., monitor, analyze, plan, and execute) control loop to facilitate closed-loop automation, and discuss the quintessential role of Artificial Intelligence/Machine Learning in its realization. We also instigate open research challenges for closed-loop automation of 5G and beyond mobile networks. • Networks → Network management; Mobile networks.
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019
Network operators must continuously scale the capacity of their optical backbone networks to keep... more Network operators must continuously scale the capacity of their optical backbone networks to keep apace with the proliferation of bandwidth-intensive applications. Today's optical networks are designed to carry large traffic aggregates with coarse-grained resource allocation, and are not adequate for maximizing utilization of the expensive optical substrate. Elastic Optical Network (EON) is an emerging technology that facilitates flexible allocation of fiber spectrum by leveraging finer-grained channel spacing, tunable modulation formats and Forward Error Correction (FEC) overheads, and baud-rate assignment, to right size spectrum allocation to customer needs. Virtual Network Embedding (VNE) over EON has been a recent topic of interest due to its importance for 5G network slicing. However, the problem has not yet been addressed while simultaneously considering the full flexibility offered by an EON. In this paper, we present an optimization model that solves the VNE problem over EON when lightpath configurations can be chosen among a large (and practical) set of combinations of paths, modulation formats, FEC overheads and baud rates. The VNE over EON problem is solved in its splittable version, which significantly increases problem complexity, but is much more likely to return a feasible solution. Given the intractability of the optimal solution, we propose a heuristic to solve larger problem instances. Key results from extensive simulations are: (i) a fully-flexible VNE can save up to 60% spectrum resources compared to that where no flexibility is exploited, and (ii) solutions of our heuristic fall in more than 90% of the cases, within 5% of the optimal solution, while executing several orders of magnitude faster.
IEEE Transactions on Network and Service Management, 2018
IEEE Journal on Selected Areas in Communications, 2018
A key challenge in network virtualization is to efficiently map a virtual network (VN) on a subst... more A key challenge in network virtualization is to efficiently map a virtual network (VN) on a substrate network (SN), while accounting for possible substrate failures. This is known as the survivable VN embedding (SVNE) problem. The state-of-the-art literature has studied the SVNE problem from infrastructure providers' (InPs') perspective, i.e., provisioning backup resources in the SN. A rather unexplored solution spectrum is to augment the VN with sufficient spare backup capacity to survive substrate failures and embed the resulting VN accordingly. Such augmentation enables InPs to offload failure recovery decisions to the VN operator, thus providing more flexible VN management. In this paper, we study the problem of jointly optimizing spare capacity allocation in a VN and embedding the VN to guarantee full bandwidth in the presence of multiple substrate link failures. We formulate the optimal solution to this problem as a quadratic integer program that we transform into an integer linear program. We also propose a heuristic algorithm to solve larger instances of the problem. Based on analytical study and simulation, our key findings are: 1) provisioning shared backup resources in the VN can yield ∼33% more resource efficient embedding compared to doing the same at the SN level and 2) our heuristic allocates ∼21% extra resources compared to the optimal, while executing several orders of magnitude faster.
Journal of Internet Services and Applications, 2018
Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problem... more Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains. Primarily, this is due to the explosion in the availability of data, significant improvements in ML techniques, and advancement in computing capabilities. Undoubtedly, ML has been applied to various mundane and complex problems arising in network operation and management. There are various surveys on ML for specific areas in networking or for specific network technologies. This survey is original, since it jointly presents the application of diverse ML techniques in various key areas of networking across different network technologies. In this way, readers will benefit from a comprehensive discussion on the different learning paradigms and ML techniques applied to fundamental problems in networking, including traffic prediction, routing and classification, congestion control, resource and fault management, QoS and QoE management, and network security. Furthermore, this survey delineates the limitations, give insights, research challenges and future opportunities to advance ML in networking. Therefore, this is a timely contribution of the implications of ML for networking, that is pushing the barriers of autonomic network operation and management.
IEEE Transactions on Network and Service Management, 2017
Network virtualization has evolved as a key enabling technology for offering the next generation ... more Network virtualization has evolved as a key enabling technology for offering the next generation network services. Recently, it is being rolled out in data center networks as a means to provide bandwidth guarantees to cloud applications. With increasing deployments of virtual networks (VNs) in commercialgrade networks with commodity hardware, VNs need to tackle failures in the underlying substrate network. In this paper, we study the problem of recovering a batch of VNs affected by a substrate node failure. The combinatorial possibilities of alternate embeddings of the failed virtual nodes and links of the VNs make the task of finding the most efficient recovery both non-trivial and intractable. Furthermore, any recovery approach ideally should not cause any service disruption for the unaffected parts of the VNs. We take into account these issues to design a generalized recovery approach that can achieve customized objectives such as fair treatment on the failed VNs, partial treatment based on priority, and so on. We provide integer linear programming (ILP) formulations for two variants of our recovery scheme, namely, fair recovery model and priority-based recovery model. We also propose a fast and scalable heuristic algorithm to tackle the computational complexity of the ILP solution. Evaluation results demonstrate that our heuristic performs close to the optimal solution and outperforms the state-of-the-art algorithm.
2016 12th International Conference on Network and Service Management (CNSM), 2016
Network virtualization (NV) has evolved as a key enabling technology for offering the next genera... more Network virtualization (NV) has evolved as a key enabling technology for offering the next generation network services. Recently, it is being rolled out in data center networks as a means to provide bandwidth guarantees to cloud applications. With increasing deployments of virtual networks (VNs) in commercial-grade networks with commodity hardware, VNs need to tackle failures in the underlying substrate network. In this paper, we study the problem of recovering a batch of VNs affected by a substrate node failure. The combinatorial possibilities of alternate embeddings of the failed virtual nodes and links of the VNs makes the task of finding the most efficient recovery both non-trivial and intractable. Furthermore, any recovery approach ideally should not cause any service disruption for the unaffected parts of the VNs. We take into account these issues to design a recovery approach for maximizing recovery and minimizing the cost of recovery and network disruption. We provide an Integer Linear Programming (ILP) formulation of our recovery scheme. We also propose a fast and scalable heuristic algorithm to tackle the computational complexity of the ILP solution. Evaluation results demonstrate that our heuristic performs close to the optimal solution and outperforms the state-of-the-art algorithm.
NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, 2016
Network virtualization is enabling infrastructure providers (InPs) to offer new services to highe... more Network virtualization is enabling infrastructure providers (InPs) to offer new services to higher level service providers (SPs). InPs are usually bound by Service Level Agreements (SLAs) to ensure various levels of resource availability for different SPs' virtual networks (VNs). They provision redundant backup resources while embedding an SP's VN request to conform to the SLAs during physical failures in the infrastructure. An extreme of this backup resource provisioning is to reserve a dedicated backup of each element in an SP's VN request. Such dedicated protection scheme can enable an InP to ensure fast VN recovery, thus, providing high uptime guarantee to the SPs. In this paper, we study the 1 + 1-Protected Virtual Network Embedding (1 + 1-ProViNE) problem. We propose Dedicated Protection for Virtual Network Embedding (DRONE), a suite of solutions to the 1 + 1-ProViNE. DRONE includes an Integer Linear Programming (ILP) formulation for optimal solution (OPT-DRONE) and a heuristic (FAST-DRONE) to tackle the computational complexity in computing the optimal solution. Trace driven simulations show that FAST-DRONE allocates only 14.3% extra backup resources on average compared to the optimal solution, while executing 200x-12000x faster.
Exploring the Behavior and Changing Trends of Rainfall and Temperature Using Statistical Computing Techniques
Computational Intelligence Techniques in Earth and Environmental Sciences, 2014
The present study aimed at quantifying the change in surface air temperature and monthly total ra... more The present study aimed at quantifying the change in surface air temperature and monthly total rainfall. The changing trend was detected using Mann–Kendall trend test, seasonal Mann–Kendall trend test, and Sen’s slope estimator. K-means clustering algorithm was used to identify the rainfall distribution patterns over the years and also their changes with time. A comparative analysis was done among different time series prediction models to find out their suitability for forecasting daily temperature in climatic condition of Bangladesh. The analysis was performed using daily temperature and rainfall data of more than last 40 years (till 2009). The study found an increasing trend in maximum temperature during June to November and in minimum temperature during December to January in Bangladesh. There has been seen no significant change in rainfall over the years. However on the western side of the country, the amount of rain is significantly less than the eastern side. The study found that different prediction models were appropriate for different conditions.
2017 IFIP Networking Conference (IFIP Networking) and Workshops, 2017
A key challenge in Network Virtualization is to efficiently map a virtual network (VN) on a subst... more A key challenge in Network Virtualization is to efficiently map a virtual network (VN) on a substrate network (SN) while accounting for possible substrate failures. This is known as the Survivable Virtual Network Embedding (SVNE) problem. The state-of-the-art literature has studied the SVNE problem from infrastructure providers' (InPs) perspective, i.e., provisioning backup resources in the SN. A rather unexplored solution spectrum is to augment the VN with sufficient spare backup capacity to survive substrate failures and embed the resulting VN accordingly. Such augmentation enables InPs to offload failure recovery decisions to the VN operator, thus, providing more flexible VN management. In this paper, we study the problem of jointly optimizing spare backup capacity allocation in a VN and embedding the VN to guarantee full bandwidth in the presence of single substrate link failure. We formulate the optimal solution to the joint optimization problem as a quadratic integer program that we transform into an integer linear program. We propose a heuristic algorithm to solve larger instances of the problem. Simulation results show that our heuristic allocates ∼21% extra resources compared to the optimal, while executing several orders of magnitude faster.
Network Virtualization (NV) is perceived as an enabling technology for the future Internet and th... more Network Virtualization (NV) is perceived as an enabling technology for the future Internet and the 5th Generation (5G) of mobile networks. It is becoming increasingly difficult to keep up with emerging applications’ Quality of Service (QoS) requirements in an ossified Internet. NV addresses the current Internet’s ossification problem by allowing the coexistence of multiple Virtual Networks (VNs), each customized to a specific purpose on the shared Internet. NV also facilitates a new business model, namely, Network-as-a-Service (NaaS), which provides a separation between applications and services, and the networks supporting them. 5G mobile network operators have adopted the NaaS model to partition their physical network resources into multiple VNs (also called network slices) and lease them to service providers. Service providers use the leased VNs to offer customized services satisfying specific QoS requirements without any investment in deploying and managing a physical network in...
Managing Virtualized Networks and Services with Machine Learning
Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning
2019 IEEE 27th International Conference on Network Protocols (ICNP)
I would also like to express my special gratitude to Nashid Shahriar and Shihabur Rahman Chowdhur... more I would also like to express my special gratitude to Nashid Shahriar and Shihabur Rahman Chowdhury for their constant help over the course of this project. I would like to extend my appreciation to Massimo Tornatore who provided his expertise and invaluable feedback on this work. Above all, I owe my deepest gratitude to my parents, Parisa and Hossein, for their unconditional love and support along this way.
Uploads
Papers by Nashid Shahriar