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Raj Jain

Publications and source records attributed to Raj Jain.

At least 37 records · Page 2Linked to original sources
arXiv2019

Analysis of Application Delivery Platform for Software Defined Infrastructures

Application Service Providers (ASPs) obtaining resources from multiple clouds have to contend with different management and control platforms employed by the cloud service providers (CSPs) and network service providers (NSP). Distributing applications on multiple clouds has a number of benefits but the absence of a common multi-cloud management platform that would allow ASPs dynamic and real-time control over resources across multiple clouds and interconnecting networks makes this task arduous. OpenADN, being developed at Washington University in Saint Louis, fills this gap. However, performance issues of such a complex, distributed and multi-threaded platform, not tackled appropriately, may neutralize some of the gains accruable to the ASPs. In this paper, we establish the need for and methods of collecting precise and fine-grained behavioral data of OpenADN like platforms that can be used to optimize their behavior in order to control operational cost, performance (e.g., latency) and energy consumption.

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arXiv2019

A Survey of Protocols and Standards for Internet of Things

The rapid growth in technology and internet connected devices has enabled Internet of Things (IoT) to be one of the important fields in computing. Standards, technologies and platforms targeting IoT ecosystem are being developed at a very fast pace. IoT enables things to communicate and coordinate decisions for many different types of applications including healthcare, home automation, disaster recovery, and industry automation. It is expected to expand to even more applications in the future. This paper surveys several standards by IEEE, IETF and ITU that enable technologies enabling the rapid growth of IoT. These standards include communications, routing, network and session layer protocols that are being developed to meet IoT requirements. The discussion also includes management and security protocols in addition to the current challenges in IoT which gives insights into the current research to solve such challenges.

cs.NI↗
arXiv2019

Exploring Micro-Services for Enhancing Internet QoS

With the enhancements in the field of software-defined networking and virtualization technologies, novel networking paradigms such as network function virtualization (NFV) and the Internet of things (IoT) are rapidly gaining ground. Development of IoT as well as 5G networks and explosion in online services has resulted in an exponential growth of devices connected to the network. As a result, application service providers (ASPs) and Internet service providers (ISPs) are being confronted with the unprecedented challenge of accommodating increasing service and traffic demands from the geographically distributed users. To tackle this problem, many ASPs and ISPs, such as Netflix, Facebook, AT&T and others are increasingly adopting micro-services (MS) application architecture. Despite the success of MS in the industry, there is no specific standard or research work for service providers as guidelines, especially from the perspective of basic micro-service operations. In this work, we aim to bridge this gap between industry and academia and discuss different micro-service deployment, discovery and communication options for service providers as a means to forming complete service chains. In addition, we address the problem of scheduling micro-services across multiple clouds, including micro-clouds. We consider different user-level SLAs, such as latency and cost, while scheduling such services. We aim to reduce overall turnaround time as well as costs for the deployment of complete end-to-end service. In this work, we present a novel affinity-based fair weighted scheduling heuristic to solve this problem. We also compare the results of proposed solution with standard greedy scheduling algorithms presented in the literature and observe significant improvements.

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arXiv2019

Fault and Performance Management in Multi-Cloud Based NFV using Shallow and Deep Predictive Structures

Deployment of Network Function Virtualization (NFV) over multiple clouds accentuates its advantages like the flexibility of virtualization, proximity to customers and lower total cost of operation. However, NFV over multiple clouds has not yet attained the level of performance to be a viable replacement for traditional networks. One of the reasons is the absence of a standard based Fault, Configuration, Accounting, Performance and Security (FCAPS) framework for the virtual network services. In NFV, faults and performance issues can have complex geneses within virtual resources as well as virtual networks and cannot be effectively handled by traditional rule-based systems. To tackle the above problem, we propose a fault detection and localization model based on a combination of shallow and deep learning structures. Relatively simpler detection of 'fault' and 'no-fault' conditions or 'manifest' and 'impending' faults have been effectively shown to be handled by shallow machine learning structures like Support Vector Machine (SVM). Deeper structure, i.e. the stacked autoencoder has been found to be useful for a more complex localization function where a large amount of information needs to be worked through, in different layers, to get to the root cause of the problem. We provide evaluation results using a dataset adapted from logs of disruption in an operator's live network fault datasets available on Kaggle and another based on multivariate kernel density estimation and Markov sampling.

cs.NI↗
arXiv2019

Optimal Virtual Network Function Placement and Resource Allocation in Multi-Cloud Service Function Chaining Architecture

Service Function Chaining (SFC) is the problem of deploying various network service instances over geographically distributed data centers and providing inter-connectivity among them. The goal is to enable the network traffic to flow smoothly through the underlying network, resulting in an optimal quality of experience to the end-users. Proper chaining of network functions leads to optimal utilization of distributed resources. This has been a de-facto model in the telecom industry with network functions deployed over underlying hardware. Though this model has served the telecom industry well so far, it has been adapted mostly to suit the static behavior of network services and service demands due to the deployment of the services directly over physical resources. This results in network ossification with larger delays to the end-users, especially with the data-centric model in which the computational resources are moving closer to end users. A novel networking paradigm, Network Function Virtualization (NFV), meets the user demands dynamically and reduces operational expenses (OpEx) and capital expenditures (CapEx), by implementing network functions in the software layer known as virtual network functions (VNFs). VNFs are then interconnected to form a complete end-to-end service, also known as service function chains (SFCs). In this work, we study the problem of deploying service function chains over network function virtualized architecture. Specifically, we study virtual network function placement problem for the optimal SFC formation across geographically distributed clouds. We set up the problem of minimizing inter-cloud traffic and response time in a multi-cloud scenario as an ILP optimization problem, along with important constraints such as total deployment costs and service level agreements (SLAs). We consider link delays and computational delays in our model.

cs.NI↗
arXiv2019

Efficient Virtual Network Function Placement Strategies for Cloud Radio Access Networks

The new generation of 5G mobile services places stringent requirements for cellular network operators in terms of latency and costs. The latest trend in radio access networks (RANs) is to pool the baseband units (BBUs) of multiple radio base stations and to install them in a centralized infrastructure, such as a cloud, for statistical multiplexing gains. The technology is known as Cloud Radio Access Network (CRAN). Since cloud computing is gaining significant traction and virtualized data centers are becoming popular as a cost-effective infrastructure in the telecommunication industry, CRAN is being heralded as a candidate technology to meet the expectations of radio access networks for 5G. In CRANs, low energy base stations (BSs) are deployed over a small geographical location and are connected to a cloud via finite capacity backhaul links. Baseband processing unit (BBU) functions are implemented on the virtual machines (VMs) in the cloud over commodity hardware. Such functions, built-in software, are termed as virtual functions (VFs). The optimized placement of VFs is necessary to reduce the total delays and minimize the overall costs to operate CRANs. Our study considers the problem of optimal VF placement over distributed virtual resources spread across multiple clouds, creating a centralized BBU cloud. We propose a combinatorial optimization model and the use of two heuristic approaches, which are, branch-and-bound (BnB) and simulated annealing (SA) for the proposed optimal placement. In addition, we propose enhancements to the standard BnB heuristic and compare the results with standard BnB and SA approaches. The proposed enhancements improve the quality of the solution in terms of latency and cost as well as reduce the execution complexity significantly.

cs.NI↗
arXiv2019

SCADA System Testbed for Cybersecurity Research Using Machine Learning Approach

This paper presents the development of a Supervisory Control and Data Acquisition (SCADA) system testbed used for cybersecurity research. The testbed consists of a water storage tank's control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naive Bayes and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environments

cs.NI↗
arXiv2018

Machine Learning for Anomaly Detection and Categorization in Multi-cloud Environments

Recently, advances in machine learning techniques have attracted the attention of the research community to build intrusion detection systems (IDS) that can detect anomalies in the network traffic. Most of the research works, however, do not differentiate among different types of attacks. This is, in fact, necessary for appropriate countermeasures and defense against attacks. In this paper, we investigate both detecting and categorizing anomalies rather than just detecting, which is a common trend in the contemporary research works. We have used a popular publicly available dataset to build and test learning models for both detection and categorization of different attacks. To be precise, we have used two supervised machine learning techniques, namely linear regression (LR) and random forest (RF). We show that even if detection is perfect, categorization can be less accurate due to similarities between attacks. Our results demonstrate more than 99% detection accuracy and categorization accuracy of 93.6%, with the inability to categorize some attacks. Further, we argue that such categorization can be applied to multi-cloud environments using the same machine learning techniques.

cs.CR↗
arXiv2018

Feasibility of Supervised Machine Learning for Cloud Security

Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. Recently, learning-based methods for security applications are gaining popularity in the literature with the advents in machine learning techniques. However, the major challenge in these methods is obtaining real-time and unbiased datasets. Many datasets are internal and cannot be shared due to privacy issues or may lack certain statistical characteristics. As a result of this, researchers prefer to generate datasets for training and testing purpose in the simulated or closed experimental environments which may lack comprehensiveness. Machine learning models trained with such a single dataset generally result in a semantic gap between results and their application. There is a dearth of research work which demonstrates the effectiveness of these models across multiple datasets obtained in different environments. We argue that it is necessary to test the robustness of the machine learning models, especially in diversified operating conditions, which are prevalent in cloud scenarios. In this work, we use the UNSW dataset to train the supervised machine learning models. We then test these models with ISOT dataset. We present our results and argue that more research in the field of machine learning is still required for its applicability to the cloud security.

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arXiv2018

Security Services Using Blockchains: A State of the Art Survey

This article surveys blockchain-based approaches for several security services. These services include authentication, confidentiality, privacy, and access control list (ACL), data and resource provenance, and integrity assurance. All these services are critical for the current distributed applications, especially due to the large amount of data being processed over the networks and the use of cloud computing. Authentication ensures that the user is who he/she claims to be. Confidentiality guarantees that data cannot be read by unauthorized users. Privacy provides the users the ability to control who can access their data. Provenance allows an efficient tracking of the data and resources along with their ownership and utilization over the network. Integrity helps in verifying that the data has not been modified or altered. These services are currently managed by centralized controllers, for example, a certificate authority. Therefore, the services are prone to attacks on the centralized controller. On the other hand, blockchain is a secured and distributed ledger that can help resolve many of the problems with centralization. The objectives of this paper are to give insights on the use of security services for current applications, to highlight the state of the art techniques that are currently used to provide these services, to describe their challenges, and to discuss how the blockchain technology can resolve these challenges. Further, several blockchain-based approaches providing such security services are compared thoroughly. Challenges associated with using blockchain-based security services are also discussed to spur further research in this area.

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arXiv2016

Perspectives on Software-Defined Networks: interviews with five leading scientists from the networking community

Software defined Networks (SDNs) have drawn much attention both from academia and industry over the last few years. Despite the fact that underlying ideas already exist through areas such as P2P applications and active networks (e.g. virtual topologies and dynamic changes of the network via software), only now has the technology evolved to a point where it is possible to scale the implementations, which justifies the high interest in SDNs nowadays. In this article, the JISA Editors invite five leading scientists from three continents (Raouf Boutaba, David Hutchison, Raj Jain, Ramachandran Ramjee, and Christian Esteve Rothenberg) to give their opinions about what is really new in SDNs. The interviews cover whether big telecom and data center companies need to consider using SDNs, if the new paradigm is changing the way computer networks are understood and taught, and what are the open issues on the topic.

cs.NI↗
arXiv2016

Survey of Important Issues in UAV Communication Networks

Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications where human lives would otherwise be endangered. Multi-UAV systems can collaboratively complete missions more efficiently and economically as compared to single UAV systems. However, there are many issues to be resolved before effective use of UAVs can be made to provide stable and reliable context-specific networks. Much of the work carried out in the areas of Mobile Ad Hoc Networks (MANETs), and Vehicular Ad Hoc Networks (VANETs) does not address the unique characteristics of the UAV networks. UAV networks may vary from slow dynamic to dynamic; have intermittent links and fluid topology. While it is believed that ad hoc mesh network would be most suitable for UAV networks yet the architecture of multi-UAV networks has been an understudied area. Software Defined Networking (SDN) could facilitate flexible deployment and management of new services and help reduce cost, increase security and availability in networks. Routing demands of UAV networks go beyond the needs of MANETS and VANETS. Protocols are required that would adapt to high mobility, dynamic topology, intermittent links, power constraints and changing link quality. UAVs may fail and the network may get partitioned making delay and disruption tolerance an important design consideration. Limited life of the node and dynamicity of the network leads to the requirement of seamless handovers where researchers are looking at the work done in the areas of MANETs and VANETs, but the jury is still out. As energy supply on UAVs is limited, protocols in various layers should contribute towards greening of the network. This article surveys the work done towards all of these outstanding issues, relating to this new class of networks, so as to spur further research in these areas.

cs.NI↗
arXiv2016

On Determining the Fair Bandwidth Share for ABR Connections in ATM Networks

In a multi-service network such as ATM, adaptive data services(such as ABR) share the bandwidth unused by higher priority services. The network indicates to the ABR sources the fair and efficient rates at which they should transmit to minimize their cell loss. In this paper, we propose a new method for determining the "effective" number of active connections, and the fair bandwidth share for each connection.

cs.NI↗
arXiv2016

Survivability in IP over WDM networks

The Internet is emerging as the new universal telecommunication medium. IP over WDM has been envisioned as one of the most attractive architectures for the new Internet. Consequently survivability is a crucial concern in designing IP over WDM networks. This paper presents a survey of the survivability mechanisms for IP over WDM networks and thus is intended to provide a summary of what has been done in this area and help further research. A number of optical layer protection techniques have been discussed. They are examined from the point of view of cost, complexity, and application. Survivability techniques are being made available at multiple layers of the network. This paper also studies the recovery features of each network layer and explains the impact of interaction between layers on survivability. The advantages and issues of multi-layer survivability have been identified. The main idea is that the optical layer can provide fast protection while the higher layers can provide intelligent restoration. With this idea in mind, a new scheme of carrying IP over WDM using MPLS or Multi Protocol Lambda-Switching has been discussed. Finally, an architecture is suggested by means of which the optical layer can perform an automatic protection switch, with priority considerations with the help of signaling from the higher layers.

cs.NI↗
arXiv2016

Achieving QoS for TCP Traffic in Satellite Networks with Differentiated Services

Satellite networks play an indispensable role in providing global Internet access and electronic connectivity. To achieve such a global communications, provisioning of quality of service (QoS) within the advanced satellite systems is the main requirement. One of the key mechanisms of implementing the quality of service is traffic management. Traffic management becomes a crucial factor in the case of satellite network because of the limited availability of their resources. Currently, Internet Protocol (IP) only has minimal traffic management capabilities and provides best effort services. In this paper, we present broadband satellite network QoS model and simulated performance results. In particular, we discuss the TCP flow aggregates performance for their good behavior in the presence of competing UDP flow aggregates in the same assured forwarding. We identify several factors that affect the performance in the mixed environments and quantify their effects using a full factorial design of experiment methodology.

cs.NI↗
arXiv2016

Multimedia Satellite Networks and TCP/IP Traffic Transport

To meet an increasing demand for multimedia services and electronic connectivity across the world, satellite networks will play an indispensable role in the deployment of global networks. The new services gaining momentum include mobile services, private intranets and high data rate internet access carried over integrated satellite-fiber networks. Several performance issues need to be addressed before a transport layer protocol, like TCP can satisfactorily work over satellite ATM for large delay-bandwidth networks. In this paper, we review the proposed satellite systems and discuss challenges such as, traffic management and QoS requirements for broadband satellite ATM networks. The performance results of TCP enhancements for Unspecified Bit Rate over ATM (ATM-UBR+) for large bandwidth-delay environments with various end system policies and drop policies for several buffer sizes are presented.

cs.NI↗
arXiv2016

An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments

Smart energy in buildings is an important research area of Internet of Things (IoT). Buildings as important parts of the smart grids, their energy efficiency is vital for the environment and global sustainability. Using a LEED-gold-certificated green office building, we built a unique IoT experimental testbed for our energy efficiency and building intelligence research. We first monitor and collect one-year-long building energy usage data and then systematically evaluate and analyze them. The results show that due to the centralized and static building controls, the actual running of green buildings may not be energy efficient even though they may be "green" by design. Inspired by "energy proportional computing" in modern computers, we propose a IoT framework with smart location-based automated and networked energy control, which uses smartphone platform and cloud computing technologies to enable multi-scale energy proportionality including building-, user-, and organizational-level energy proportionality. We further build a proof-of-concept IoT network and control system prototype and carried out real-world experiments which demonstrate the effectiveness of the proposed solution. We envision that the broad application of the proposed solution has not only led to significant economic benefits in term of energy saving, improving home/office network intelligence, but also bought in a huge social implication in terms of global sustainability.

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