A genetic algorithm-based flow update scheduler for software-defined networks Mohammad Reza Abbasi, Ajay Guleria, Mandalika Syamala Devi International Journal of Communication Systems, 2020 Summary Software‐defined networking (SDN) facilitates network programmability through a central controller. It dynamically modifies the network configuration to adapt to the changes in the network. In SDN, the controller updates the network configuration through flow updates, ie, installing the flow rules in network devices. However, during the network update, improper scheduling of flow updates can lead to a number of problems including overflowing of the switch flow table memory and the link bandwidth. Another challenge is minimizing the network update completion time during large‐network updates triggered by events such as traffic engineering path updates. The existing centralized approaches do not search the solution space for flow update schedules with optimal completion time. We proposed a hybrid genetic algorithm‐based flow update scheduling method (the GA‐Flow Scheduler). By searching the solution space, the GA‐Flow Scheduler attempts to minimize the completion time of the network update without overflowing the flow table memory of the switches and the link bandwidth. It can be used in combination with other existing flow scheduling methods to improve the network performance and reduce the flow update completion time. In this paper, the GA‐Flow Scheduler is combined with a stand‐alone method called the three‐step method. Through large‐scale experiments, we show that the proposed hybrid approach could reduce the network update time and packet loss. It is concluded that the proposed GA‐Flow Scheduler provides improved performance over the stand‐alone three‐step method. Also, it handles the above‐mentioned network update problems in SDN.
SDN-based Mobility Management and QoS Support for Vehicular Ad-hoc Networks Kuldip Singh Atwal, Ajay Guleria, Mostafa Bassiouni 2018 International Conference on Computing Networking and Communications Icnc 2018, 2018 Along with non-safety related applications, traffic safety is the major concern of the Vehicular Ad-hoc Networks (VANETs). However, the mobility management due to the high speed of vehicles, intermittent connectivity, and frequent topology variations are some of the crucial roadblocks. These challenges impose setback for quality of service (QoS) guarantee that leads to unfulfilled goals of VANETs deployment. The centralized control of the Software-Defined Networking (SDN) paradigm allows optimum utilization of global network view to meet the QoS requirements. Furthermore, by a systematic design of the SDN control plane, the issues of mobility management and poor network connectivity can also be addressed in an efficient manner. In this paper, we propose an SDN-based architecture that utilizes cloud computing and deals with inherent constraints of VANETs. A logically distributed control plane is devised for seamless connectivity, mobility management, and QoS support. The proposed model achieves optimum performance and robustness against failures by harnessing capabilities of SDN and cloud computing. We implemented the QoS and routing applications to evaluate the proposed model. The comparative experimental results are presented to demonstrate the effectiveness of the proposed framework.
An overview of flow-based anomaly detection Rohini Sharma, Ajay Guleria, R.K. Singla International Journal of Communication Networks and Distributed Systems, 2018 Intrusions in computer networks are handled using misuse or anomaly-based solutions. Deep packet inspection is generally incorporated in solutions for better detection and mitigation but with the growth of networks at exponential speed, it has become an expensive solution and makes real-time detection difficult. In this paper, network flows-based anomaly detection techniques are reviewed. The review starts with motivation behind using network flows and justifies why flow-based anomaly detection is the need of the hour. Flow-based datasets are also investigated and reviewed. The main focus is on techniques and methodologies used by researchers for anomaly detection in computer networks. The techniques reviewed are categorised into five classes: statistical, machine learning, clustering, frequent pattern mining and agent-based. At the end the core research problems and open challenges are discussed.
Characterizing network flows for detecting DNS, NTP, and SNMP anomalies Rohini Sharma, Ajay Guleria, R. K. Singla Advances in Intelligent Systems and Computing, 2018 Network security can never be assured fully as new attacks are reported every day. Characterizing such new attacks is a challenging task. For detecting anomalies based on specific services, it is desirable to find characteristic features for those service specific anomalies. In this paper, real-time flow-based network traffic captured from a university campus is studied to find if the traditional volume-based analysis of aggregated flows and service specific aggregated flows is useful in detecting service specific anomalies or not. Two existing techniques are also evaluated to find characteristic features of these anomalies. The service specific anomalies: DNS, NTP, and SNMP are considered for study in this paper.
A New Labeled Flow-based DNS Dataset for Anomaly Detection: PUF Dataset Rohini Sharma, R.K. Singla, Ajay Guleria Procedia Computer Science, 2018 Flow-based anomaly detection is gaining momentum because it can be deployed for real time detection as it analyses only packet headers. To evaluate anomaly detection techniques, labeled dataset is required as unlabeled dataset is not useful for the evaluation. Many packet based network traffic datasets are available but flow-based datasets are sparsely available. In this paper, we present a comprehensive review of the existing flow-based datasets, making emphasis on their main shortcomings. Then a new labeled flow-based DNS dataset viz. PUF Dataset is presented for detecting compromised hosts in a network. The dataset consists of real flows captured from the Computer Centre of Panjab University that handles the entire campus network. All the flows are labeled using logs which are captured for the signatures implemented in Intrusion Prevention System. The implemented signatures are for DNS anomalies. The final dataset consists of 298463 flows with 260343 benign and 38120 anomalous flows. Profiles have been generated for sub-networks for benign as well as anomalous flows using both statistically derived and entropy based features. These profiles can be used to detect anomalous sub-networks thereby helping to isolate compromised host(s).
Position based adaptive routing for VANETs Ajay Guleria, Kuldeep Singh International Journal of Computer Networks and Communications, 2017 Routing plays a very significant role in multi hop data dissemination in Vehicular Ad-Hoc Networks (VANETs). Wehave proposed a Position based Adaptive Routing (PAR) protocol which is scalable for different network densities in VANETs. This scheme uses Preferred Group Broadcasting (PGB) for route discovery. In this mode, after broadcasting the request for route discovery the source node starts listening to the channel. If the packet is not further rebroadcasted by any neighbor in a set timeout, then it repeats the broadcast. This process is repeated until the request reaches the destination. The destination keeps on accumulating route requests coming from different paths until predefined time. It then chooses the least cost path as route reply. It uses the set of traversed anchors for sending the unicast route reply to the source node. PAR uses Advance Greedy Forwarding (AGF) for data forwarding and greedily forwards the data packet to the next anchor towards destination node. It switches to carry and forward mode once it finds partitions in the network. The intermediate vehicle buffers the packet until next junction and switches back to position based scheme and greedily forwards to next node in range which is closest to the destination. To have an end to end connectedpath, it uses guards to guard anchors tied to different junction and geographical locations in the network. The algorithm is scalable and exploits advantages of existing techniques already developed for specific scenarios in VANET. Results show that the service ratio and packet delay of PAR are higher than its counterparts.
A scalable peer-to-peer control plane architecture for Software Defined Networks Kuldip Singh Atwal, Ajay Guleria, Mostafa Bassiouni Proceedings 2016 IEEE 15th International Symposium on Network Computing and Applications NCA 2016, 2016 Control plane scalability is one of the major concerns in Software Defined Networking (SDN) deployment. Although the centralization of the control plane by decoupling it from the data plane facilitates ease of network management, however, it introduces new challenges. One of these challenges is to maintain performance, consistency, and scalability while minimizing the corresponding overheads. In this paper, we propose an architecture that allows the control plane to evolve at a hyper-scale level as well as address important performance and reliability issues. A hierarchical control plane architecture with peer-to-peer communication among logically distributed controllers is designed with the goal of achieving optimum performance and consistency gains while mitigating overheads. A root controller is deployed at the top layer of the hierarchy to maintain global network view. The proposed model is helpful in improving network robustness against failures and supporting a desired level of reliability. To evaluate our model, we developed a realistic emulation platform using ONOS, FlowVisor, Mininet, and Open vSwitch. The proposed architecture is compared with earlier solutions and experimental results are presented to demonstrate the effectiveness of the proposed model.
Traffic engineering in software defined networks: A survey Journal of Telecommunications and Information Technology, 2016
On demand data dissemination for differentiated levels of priorities in VANETS International Journal of Innovative Computing Information and Control, 2014
RECENT SCHOLAR PUBLICATIONS
Intent-Based Networking and Traffic Engineering for Automated Management of Bursty Massive Machine-Type Communications D Snowden, A Guleria, N Han, S Kuklinski, R Poorzare, Y Zhang, G Maia 2026
Fairness-Aware Traffic Engineering Policies for Competing Massive Data Flows in Multi-Tenant Cloud Data Centers J Bushman, M Roughan, DL Guidoni, T Otoshi, A Guleria, X Wang 2026
Machine Learning Based Approach for Evaluating Agile Based Methods to Enhance Software Quality AG Neha Saini, Indu Chhabra International Journal of Engineering and Advanced Technology 12 (2), 123-127 , 2022 2022
Anomaly detection systems using IP flows: A review R Bhatia, R Sharma, A Guleria Advances in Clean Energy Technologies: Select Proceedings of ICET 2020, 1035 … , 2021 2021 Citations: 5
Flow-based profile generation and network traffic detection for DNS anomalies using optimised entropy-based features selection and modified Holt Winter's method R Sharma, A Guleria, RK Singla International Journal of Security and Networks 16 (4), 244-257 , 2021 2021 Citations: 3
Integrated Intrusion Detection Scheme using Agents K Rai, A Guleria, MS Devi International Journal of Cyber-Security and Digital Forensics 9 (1), 26-42 , 2020 2020 Citations: 1
A genetic algorithm‐based flow update scheduler for software‐defined networks MR Abbasi, A Guleria, MS Devi International Journal of Communication Systems 33 (2), e4188 , 2019 2019 Citations: 1
A New Labeled Flow-based DNS Dataset for Anomaly Detection: PUF Dataset R Sharma, RK Singla, A Guleria Procedia Computer Science 132, 1458-1466 , 2018 2018 Citations: 35
SDN-based mobility management and QoS support for vehicular ad-hoc networks KS Atwal, A Guleria, M Bassiouni 2018 International conference on computing, networking and communications … , 2018 2018 Citations: 32
An overview of flow-based anomaly detection RKS Rohini Sharma, Ajay Guleria International Journal of Communication Networks and Distributed Systems 21 … , 2018 2018 Citations: 25
Packet-based Anomaly Detection using n-gram Approach K Rai, MS Devi, A Guleria International Journal of Computer Sciences and Engineering 6 (5), 366-372 , 2018 2018 Citations: 6
Characterizing Network Flows for Detecting DNS, NTP, and SNMP Anomalies RKS Rohini Sharma, Ajay Guleria Advances in Intelligent Systems and Computing 673, 327-340 , 2018 2018 Citations: 7
POSITION BASED ADAPTIVE ROUTING FOR VANETS KS Ajay Guleria International Journal of Computer Networks and Communications 9 (1), 55-70 , 2017 2017 Citations: 8
A scalable peer-to-peer control plane architecture for software defined networks KS Atwal, A Guleria, M Bassiouni 2016 IEEE 15th International Symposium on Network Computing and Applications … , 2016 2016 Citations: 14
Traffic Engineering in Software Defined Networks: A Survey MSD Mohammad R. Abbasi, Ajay Guleria Journal of Telecommunications and Information Technology 4 (2016), 3-14 , 2016 2016 Citations: 65
Decision Tree Based Algorithm for Intrusion Detection AG Kajal Rai, M Syamla Devi Int. J. Advanced Networking and Applications 7 (4), 2828-2834 , 2016 2016 Citations: 244
QoS aware service scheduling scheme for VANETs A Guleria, K Singh, N Chand International Journal of Distributed Sensor Networks 2015, 11 , 2015 2015 Citations: 5
On Demand Data Dissemination for Differentiated Levels of Priorities in VANETs A Guleria, N Chand, L Kumar International Journal of Innovative Computing, Information and Control 10 (1 … , 2014 2014 Citations: 5
Integrated Push Pull Algorithm with Accomplishment Assurance in VANETs A Guleria, NC Kaushal, LK Awasthi International Journal of Next-Generation Computing 3 (3), 274-287 , 2012 2012
Request Analysis and Dynamic Queuing System for VANETs A Guleria, N Chand, M Kumar, L Awasthi International Journal of Advanced Computer Science and Applications 3 (10 … , 2012 2012 Citations: 2
MOST CITED SCHOLAR PUBLICATIONS
Decision Tree Based Algorithm for Intrusion Detection AG Kajal Rai, M Syamla Devi Int. J. Advanced Networking and Applications 7 (4), 2828-2834 , 2016 2016 Citations: 244
Traffic Engineering in Software Defined Networks: A Survey MSD Mohammad R. Abbasi, Ajay Guleria Journal of Telecommunications and Information Technology 4 (2016), 3-14 , 2016 2016 Citations: 65
A New Labeled Flow-based DNS Dataset for Anomaly Detection: PUF Dataset R Sharma, RK Singla, A Guleria Procedia Computer Science 132, 1458-1466 , 2018 2018 Citations: 35
SDN-based mobility management and QoS support for vehicular ad-hoc networks KS Atwal, A Guleria, M Bassiouni 2018 International conference on computing, networking and communications … , 2018 2018 Citations: 32
An overview of flow-based anomaly detection RKS Rohini Sharma, Ajay Guleria International Journal of Communication Networks and Distributed Systems 21 … , 2018 2018 Citations: 25
A scalable peer-to-peer control plane architecture for software defined networks KS Atwal, A Guleria, M Bassiouni 2016 IEEE 15th International Symposium on Network Computing and Applications … , 2016 2016 Citations: 14
POSITION BASED ADAPTIVE ROUTING FOR VANETS KS Ajay Guleria International Journal of Computer Networks and Communications 9 (1), 55-70 , 2017 2017 Citations: 8
Characterizing Network Flows for Detecting DNS, NTP, and SNMP Anomalies RKS Rohini Sharma, Ajay Guleria Advances in Intelligent Systems and Computing 673, 327-340 , 2018 2018 Citations: 7
Packet-based Anomaly Detection using n-gram Approach K Rai, MS Devi, A Guleria International Journal of Computer Sciences and Engineering 6 (5), 366-372 , 2018 2018 Citations: 6
Anomaly detection systems using IP flows: A review R Bhatia, R Sharma, A Guleria Advances in Clean Energy Technologies: Select Proceedings of ICET 2020, 1035 … , 2021 2021 Citations: 5
QoS aware service scheduling scheme for VANETs A Guleria, K Singh, N Chand International Journal of Distributed Sensor Networks 2015, 11 , 2015 2015 Citations: 5
On Demand Data Dissemination for Differentiated Levels of Priorities in VANETs A Guleria, N Chand, L Kumar International Journal of Innovative Computing, Information and Control 10 (1 … , 2014 2014 Citations: 5
Flow-based profile generation and network traffic detection for DNS anomalies using optimised entropy-based features selection and modified Holt Winter's method R Sharma, A Guleria, RK Singla International Journal of Security and Networks 16 (4), 244-257 , 2021 2021 Citations: 3
Request Analysis and Dynamic Queuing System for VANETs A Guleria, N Chand, M Kumar, L Awasthi International Journal of Advanced Computer Science and Applications 3 (10 … , 2012 2012 Citations: 2
Integrated Intrusion Detection Scheme using Agents K Rai, A Guleria, MS Devi International Journal of Cyber-Security and Digital Forensics 9 (1), 26-42 , 2020 2020 Citations: 1
A genetic algorithm‐based flow update scheduler for software‐defined networks MR Abbasi, A Guleria, MS Devi International Journal of Communication Systems 33 (2), e4188 , 2019 2019 Citations: 1
Intent-Based Networking and Traffic Engineering for Automated Management of Bursty Massive Machine-Type Communications D Snowden, A Guleria, N Han, S Kuklinski, R Poorzare, Y Zhang, G Maia 2026
Fairness-Aware Traffic Engineering Policies for Competing Massive Data Flows in Multi-Tenant Cloud Data Centers J Bushman, M Roughan, DL Guidoni, T Otoshi, A Guleria, X Wang 2026
Machine Learning Based Approach for Evaluating Agile Based Methods to Enhance Software Quality AG Neha Saini, Indu Chhabra International Journal of Engineering and Advanced Technology 12 (2), 123-127 , 2022 2022
Integrated Push Pull Algorithm with Accomplishment Assurance in VANETs A Guleria, NC Kaushal, LK Awasthi International Journal of Next-Generation Computing 3 (3), 274-287 , 2012 2012
