Cloud is in the air. More and More companies and personals are connecting to cloud with so many variety
of offering provided by the companies. The cloud services are based on Internet i.e. TCP/IP. The paper
discusses limitations of one of the main existing network management protocol i.e. Simple Network
Management Protocol (SNMP) with respect to the current network conditions. The network traffic is
growing at a high speed. When we talk about the networked environment of cloud, the monitoring tool
should be capable of handling the traffic tribulations efficiently and represent a correct scenario of the
network condition. The proposed Model ‘Cloud Network Management Model (CNMM)’ provides a
comprehensive solution to manage the growing traffic in cloud and trying to improve communication of
manager and agents as in SNMP (the traditional TCP/IP network management protocol). Firstly CNMM
concentrates on reduction of packet exchange between manager and agent. Secondly it eliminates the
counter problems exist in SNMP by having periodic updates from agent without querying by the manager.
For better management we are including managers using virtualized technology. CNMM is a proposed
model with efficient communication, secure packet delivery and reduced traffic. Though the proposed
model supposed to manage the cloud traffic in a better and efficient way, the model is still a theoretical
study, its implementation and results are yet to discover. The model however is the first step towards
development of supported algorithms and protocol. Our further study will concentrate on development of
supported algorithms.
HOST AND NETWORK SECURITY by ThesisScientist.comProf Ansari
Network management means different things to different people. In some cases, it involves a solitary network consultant monitoring network activity with an outdated protocol analyzer. In other cases, network management involves a distributed database, auto polling of network devices, and high-end workstations generating real-time graphical views of network topology changes and traffic. In general, network management is a service that employs a variety of tools, applications, and devices to assist human network managers in monitoring and maintaining networks.
Overview of Network Programming, Remote Procedure Calls, Remote Method Invocation, Message Oriented Communication, and web services in distributed systems
UNIT I INTRODUCTION 7
Examples of Distributed Systems–Trends in Distributed Systems – Focus on resource sharing – Challenges. Case study: World Wide Web.
Computer network is a distributed system consisting of loosely coupled computers and other
devices. Any two of these devices, which we will from now on refer to as network elements or
transmitting elements, can communicate with each other through a communication medium. In
order for these connected devices to be considered a communicating network, there must be a set
of communicating rules or protocols each device in the network must follow to communicate wit
another device in the network. The resulting combination consisting of hardware and software is a computer communication network or computer network in short. Figure 1.1 shows a computer
network
HOST AND NETWORK SECURITY by ThesisScientist.comProf Ansari
Network management means different things to different people. In some cases, it involves a solitary network consultant monitoring network activity with an outdated protocol analyzer. In other cases, network management involves a distributed database, auto polling of network devices, and high-end workstations generating real-time graphical views of network topology changes and traffic. In general, network management is a service that employs a variety of tools, applications, and devices to assist human network managers in monitoring and maintaining networks.
Overview of Network Programming, Remote Procedure Calls, Remote Method Invocation, Message Oriented Communication, and web services in distributed systems
UNIT I INTRODUCTION 7
Examples of Distributed Systems–Trends in Distributed Systems – Focus on resource sharing – Challenges. Case study: World Wide Web.
Computer network is a distributed system consisting of loosely coupled computers and other
devices. Any two of these devices, which we will from now on refer to as network elements or
transmitting elements, can communicate with each other through a communication medium. In
order for these connected devices to be considered a communicating network, there must be a set
of communicating rules or protocols each device in the network must follow to communicate wit
another device in the network. The resulting combination consisting of hardware and software is a computer communication network or computer network in short. Figure 1.1 shows a computer
network
Checkpointing and Rollback Recovery Algorithms for Fault Tolerance in MANETs:...Eswar Publications
Mobile Ad Hoc Networks (MANETs) are emerging as a major technology in mobile computing. A MANET is a collection of mobile devices or nodes that communicate with each other using wireless links without availability of any static infrastructure or centralized control. A node in such a network should be fault tolerable and failure free execution of processes on the network nodes is vital. In order to make devices fault tolerant checkpoint based recovery technique can be used. Checkpointing is a technique that can be used to make device or node fault tolerant and reduce the recovery time in case of failure. It takes the snapshot of current application state of process and stores it in some memory area and then using it to resume the computation from current checkpoint instead of resuming it from the beginning. Some limitations of MANETs such as mobility, dynamic topology,
limited bandwidth of channel, limited storage space and power restrictions makes checkpointing as a major challenge in mobile ad hoc networks. This paper presents the survey of some existing algorithms, which have been proposed for making MANETs fault tolerant and implementing or deploying checkpointing in mobile ad hoc network.
Decrease in hardware costs and advances in computer networking technologies have led to increased interest in
the use of large-scale parallel and distributed computing systems. Distributed computing systems offer the potential for improved performance and resource sharing. In this paper we have made an overview on distributed computing. In this paper we studied the difference between parallel and distributed computing, terminologies used in distributed computing, task allocation in distributed computing and performance parameters in distributed computing system, parallel distributed algorithm models, and advantages of distributed computing and scope of distributed computing.
The Concept of Load Balancing Server in Secured and Intelligent NetworkIJAEMSJORNAL
Hundreds and thousands of data packets are routed every second by computer networks which are complex systems. The data should be routed efficiently to handle large amounts of data in network. A core networking solution which is responsible for distribution of incoming traffic among servers hosting the same content is load balancing. For example, if there are ten servers within a network and two of them are doing 95% of the work, the network is not running very efficiently. If each server was handling about 10% of the traffic, the network would run much faster.Networks get more efficient with the help of Load balancing. The traffic is evenly distributed amongst the network making sure no single device is overwhelmed.When a request is balanced across multiple servers, it prevents any server from becoming a single point of failure. It improves overall availability and responsiveness. To evenly split the traffic load among several different servers web servers; often use load balancing.Load balancing requires hardware or software that divides incoming traffic amongst the available serverseither it is done on a local network or a large web server. High amount of traffic is received by a network that have one server dedicated to balance the load among other servers and devices in the network. This server is often known as load balancer. Load balancing is used by clusters or multiple computers that work together, to spread out processing jobs among the available systems.
Lecture 01 - Chapter 1 (Part 01): This Lecture show the Overview of Course, What is an Operating System, Operating System Functions, Definition of a Distributed System, Properties of Distributed Systems, Software Concepts, Transparency in a Distributed System, Challenges, Approaches, Scalability Problems, Scalability Examples, Web Search, Financial Transactions, Multiplayer Games. Some basic concept of Operating System (OS).
Network Monitoring and Traffic Reduction using Multi-Agent TechnologyEswar Publications
In this paper the algorithms which could improve Transmission band and Network Traffic reduction for computer network has been shown. Problem solving is an area with which many Multiagent-based applications are concerned. Multiagent systems are computational systems in which several agents interact or work together to achieve some purposes. It includes distributed solutions to problems, solving distributed problems and distributed techniques for problem solving. Multiagent using for maximizing group performance with planning, execution, monitoring, communication and coordination. This paper also addresses some critical issues in developing
Multi agent-based traffic control and monitoring systems, such as interoperability, flexibility, and extendibility. Finally, several future research directions toward the successful deployment of Multiagent technology in traffic control and monitoring systems are discussed.
Optimal software-defined network topology for distributed denial of service a...journalBEEI
Distributed denial of service (DDoS) attacks are a major threat to all internet services. The main goal is to disrupt normal traffic and overwhelms the target. Software-defined networking (SDN) is a new type of network architecture where control and data plane are separated. A successful attack may block the SDN controller which may stop processing the new request and will lead to a total disruption of the whole network. The main goal of this paper is to find the optimal network topology and size which can handle Distributed denial of service attack without management channel bandwidth exhaustion or run out of SDN controller CPU and memory. Through simulations, it is shown that mesh topologies with more connections between switches are more resistant to DDoS attacks than liner type network topologies.
A MECHANISM FOR EARLY DETECTING DDOS ATTACKS BASED ON M/G/R PS QUEUEIJNSA Journal
When service system is under DDoS attacks, it is important to detect anomaly signature at starting time of attack for timely applying prevention solutions. However, early DDoS detection is difficult task because the velocity of DDoS attacks is very high. This paper proposes a DDoS attack detection method by modeling service system as M/G/R PS queue and calculating monitoring parameters based on the model in odder to
early detect symptom of DDoS attacks. The proposed method is validated by experimental system and it gives good results.
Analysis of IT Monitoring Using Open Source Software Techniques: A ReviewIJERD Editor
The Network administrators usually rely on generic and built-in monitoring tools for network
security. Ideally, the network infrastructure is supposed to have carefully designed strategies to scale up
monitoring tools and techniques as the network grows, over time. Without this, there can be network
performance challenges, downtimes due to failures, and most importantly, penetration attacks. These can lead to
monetary losses as well as loss of reputation. Thus, there is a need for best practices to monitor network
infrastructure in an agile manner. Network security monitoring involves collecting network packet data,
segregating it among all the 7 OSI layers, and applying intelligent algorithms to get answers to security-related
questions. The purpose is to know in real-time what is happening on the network at a detailed level, and
strengthen security by hardening the processes, devices, appliances, software policies, etc. The Multi Router
Traffic Grapher, or just simply MRTG, is free software for monitoring and measuring the traffic load
on network links. It allows the user to see traffic load on a network over time in graphical form.
A COMPREHENSIVE SOLUTION TO CLOUD TRAFFIC TRIBULATIONSijwscjournal
Cloud computing is generally believed to the most gifted technological revolution in computing and it will soon become an industry standard. It is believed that cloud will replace the traditional office setup. However a big question mark exists over the network performance when the cloud traffic explodes. We call it “explosion” as in future we know that various cloud services replacing desktop computing will be accessed via cloud and the traffic increases exponentially. This journal aims at addressing some of these doubts better called “dangers” about the network performance, when cloud becomes a standard globally and providing a comprehensive solution to those problems. Our study concentrates on, that despite of offering better round-trip times and throughputs, cloud appears to consistently lose large amounts of the data that it is required to send to the clients. In this journal, we give a concise survey on the research efforts in this area. Our survey findings show that the networking research community has converged to the common understanding that a measurement infrastructure is insufficient for the optimal operation and future growth of the cloud. Despite many proposals on building an network measurement infrastructure from the research community, we believe that it will not be in the near future for such an infrastructure to be fully deployed and operational, due to both the scale and the complexity of the network. We also suggest a set of technologies to identify and manage cloud traffic using IP header DS field, QoS protocols, MPLS/IP Header Compression, Use of high speed edge routers and cloud traffic flow measurement. In the solution DS Field of IP header will be used to recognize the cloud traffic separately, QOS protocols provide the cloud traffic, the type of QOS it requires by allocating resources and marking cloud traffic identification. Further the MPLS/IP Header Compression is performed so that the traffic can pass through the existing network efficiently and speedily. The solution also suggests deployment of high speed edge routers to improve network conditions and finally it suggest to measure the traffic flow using meters for better cloud network management. Our solutions assume that cloud is being assessed via basic public network.
A COMPREHENSIVE SOLUTION TO CLOUD TRAFFIC TRIBULATIONSijwscjournal
Cloud computing is generally believed to the most gifted technological revolution in computing and it will soon become an industry standard. It is believed that cloud will replace the traditional office setup. However a big question mark exists over the network performance when the cloud traffic explodes. We
call it “explosion” as in future we know that various cloud services replacing desktop computing will be accessed via cloud and the traffic increases exponentially. This journal aims at addressing some of these doubts better called “dangers” about the network performance, when cloud becomes a standard globally and providing a comprehensive solution to those problems. Our study concentrates on, that despite of offering better round-trip times and throughputs, cloud appears to consistently lose large amounts of the data that it is required to send to the clients. In this journal, we give a concise survey on the research efforts in this area. Our survey findings show that the networking research community has converged to the common understanding that a measurement infrastructure is insufficient for the optimal operation and future growth of the cloud. Despite many proposals on building an network measurement infrastructure from the research community, we believe that it will not be in the near future for such an
infrastructure to be fully deployed and operational, due to both the scale and the complexity of the network. We also suggest a set of technologies to identify and manage cloud traffic using IP header DS field, QoS protocols, MPLS/IP Header Compression, Use of high speed edge routers and cloud traffic flow measurement. In the solution DS Field of IP header will be used to recognize the cloud traffic separately, QOS protocols provide the cloud traffic, the type of QOS it requires by allocating resources and marking cloud traffic identification. Further the MPLS/IP Header Compression is performed so that the traffic can pass through the existing network efficiently and speedily. The solution also suggests deployment of high speed edge routers to improve network conditions and finally it suggest to measure the traffic flow using meters for better cloud network management. Our solutions assume that cloud is being assessed via basic public network.
Checkpointing and Rollback Recovery Algorithms for Fault Tolerance in MANETs:...Eswar Publications
Mobile Ad Hoc Networks (MANETs) are emerging as a major technology in mobile computing. A MANET is a collection of mobile devices or nodes that communicate with each other using wireless links without availability of any static infrastructure or centralized control. A node in such a network should be fault tolerable and failure free execution of processes on the network nodes is vital. In order to make devices fault tolerant checkpoint based recovery technique can be used. Checkpointing is a technique that can be used to make device or node fault tolerant and reduce the recovery time in case of failure. It takes the snapshot of current application state of process and stores it in some memory area and then using it to resume the computation from current checkpoint instead of resuming it from the beginning. Some limitations of MANETs such as mobility, dynamic topology,
limited bandwidth of channel, limited storage space and power restrictions makes checkpointing as a major challenge in mobile ad hoc networks. This paper presents the survey of some existing algorithms, which have been proposed for making MANETs fault tolerant and implementing or deploying checkpointing in mobile ad hoc network.
Decrease in hardware costs and advances in computer networking technologies have led to increased interest in
the use of large-scale parallel and distributed computing systems. Distributed computing systems offer the potential for improved performance and resource sharing. In this paper we have made an overview on distributed computing. In this paper we studied the difference between parallel and distributed computing, terminologies used in distributed computing, task allocation in distributed computing and performance parameters in distributed computing system, parallel distributed algorithm models, and advantages of distributed computing and scope of distributed computing.
The Concept of Load Balancing Server in Secured and Intelligent NetworkIJAEMSJORNAL
Hundreds and thousands of data packets are routed every second by computer networks which are complex systems. The data should be routed efficiently to handle large amounts of data in network. A core networking solution which is responsible for distribution of incoming traffic among servers hosting the same content is load balancing. For example, if there are ten servers within a network and two of them are doing 95% of the work, the network is not running very efficiently. If each server was handling about 10% of the traffic, the network would run much faster.Networks get more efficient with the help of Load balancing. The traffic is evenly distributed amongst the network making sure no single device is overwhelmed.When a request is balanced across multiple servers, it prevents any server from becoming a single point of failure. It improves overall availability and responsiveness. To evenly split the traffic load among several different servers web servers; often use load balancing.Load balancing requires hardware or software that divides incoming traffic amongst the available serverseither it is done on a local network or a large web server. High amount of traffic is received by a network that have one server dedicated to balance the load among other servers and devices in the network. This server is often known as load balancer. Load balancing is used by clusters or multiple computers that work together, to spread out processing jobs among the available systems.
Lecture 01 - Chapter 1 (Part 01): This Lecture show the Overview of Course, What is an Operating System, Operating System Functions, Definition of a Distributed System, Properties of Distributed Systems, Software Concepts, Transparency in a Distributed System, Challenges, Approaches, Scalability Problems, Scalability Examples, Web Search, Financial Transactions, Multiplayer Games. Some basic concept of Operating System (OS).
Network Monitoring and Traffic Reduction using Multi-Agent TechnologyEswar Publications
In this paper the algorithms which could improve Transmission band and Network Traffic reduction for computer network has been shown. Problem solving is an area with which many Multiagent-based applications are concerned. Multiagent systems are computational systems in which several agents interact or work together to achieve some purposes. It includes distributed solutions to problems, solving distributed problems and distributed techniques for problem solving. Multiagent using for maximizing group performance with planning, execution, monitoring, communication and coordination. This paper also addresses some critical issues in developing
Multi agent-based traffic control and monitoring systems, such as interoperability, flexibility, and extendibility. Finally, several future research directions toward the successful deployment of Multiagent technology in traffic control and monitoring systems are discussed.
Optimal software-defined network topology for distributed denial of service a...journalBEEI
Distributed denial of service (DDoS) attacks are a major threat to all internet services. The main goal is to disrupt normal traffic and overwhelms the target. Software-defined networking (SDN) is a new type of network architecture where control and data plane are separated. A successful attack may block the SDN controller which may stop processing the new request and will lead to a total disruption of the whole network. The main goal of this paper is to find the optimal network topology and size which can handle Distributed denial of service attack without management channel bandwidth exhaustion or run out of SDN controller CPU and memory. Through simulations, it is shown that mesh topologies with more connections between switches are more resistant to DDoS attacks than liner type network topologies.
A MECHANISM FOR EARLY DETECTING DDOS ATTACKS BASED ON M/G/R PS QUEUEIJNSA Journal
When service system is under DDoS attacks, it is important to detect anomaly signature at starting time of attack for timely applying prevention solutions. However, early DDoS detection is difficult task because the velocity of DDoS attacks is very high. This paper proposes a DDoS attack detection method by modeling service system as M/G/R PS queue and calculating monitoring parameters based on the model in odder to
early detect symptom of DDoS attacks. The proposed method is validated by experimental system and it gives good results.
Analysis of IT Monitoring Using Open Source Software Techniques: A ReviewIJERD Editor
The Network administrators usually rely on generic and built-in monitoring tools for network
security. Ideally, the network infrastructure is supposed to have carefully designed strategies to scale up
monitoring tools and techniques as the network grows, over time. Without this, there can be network
performance challenges, downtimes due to failures, and most importantly, penetration attacks. These can lead to
monetary losses as well as loss of reputation. Thus, there is a need for best practices to monitor network
infrastructure in an agile manner. Network security monitoring involves collecting network packet data,
segregating it among all the 7 OSI layers, and applying intelligent algorithms to get answers to security-related
questions. The purpose is to know in real-time what is happening on the network at a detailed level, and
strengthen security by hardening the processes, devices, appliances, software policies, etc. The Multi Router
Traffic Grapher, or just simply MRTG, is free software for monitoring and measuring the traffic load
on network links. It allows the user to see traffic load on a network over time in graphical form.
A COMPREHENSIVE SOLUTION TO CLOUD TRAFFIC TRIBULATIONSijwscjournal
Cloud computing is generally believed to the most gifted technological revolution in computing and it will soon become an industry standard. It is believed that cloud will replace the traditional office setup. However a big question mark exists over the network performance when the cloud traffic explodes. We call it “explosion” as in future we know that various cloud services replacing desktop computing will be accessed via cloud and the traffic increases exponentially. This journal aims at addressing some of these doubts better called “dangers” about the network performance, when cloud becomes a standard globally and providing a comprehensive solution to those problems. Our study concentrates on, that despite of offering better round-trip times and throughputs, cloud appears to consistently lose large amounts of the data that it is required to send to the clients. In this journal, we give a concise survey on the research efforts in this area. Our survey findings show that the networking research community has converged to the common understanding that a measurement infrastructure is insufficient for the optimal operation and future growth of the cloud. Despite many proposals on building an network measurement infrastructure from the research community, we believe that it will not be in the near future for such an infrastructure to be fully deployed and operational, due to both the scale and the complexity of the network. We also suggest a set of technologies to identify and manage cloud traffic using IP header DS field, QoS protocols, MPLS/IP Header Compression, Use of high speed edge routers and cloud traffic flow measurement. In the solution DS Field of IP header will be used to recognize the cloud traffic separately, QOS protocols provide the cloud traffic, the type of QOS it requires by allocating resources and marking cloud traffic identification. Further the MPLS/IP Header Compression is performed so that the traffic can pass through the existing network efficiently and speedily. The solution also suggests deployment of high speed edge routers to improve network conditions and finally it suggest to measure the traffic flow using meters for better cloud network management. Our solutions assume that cloud is being assessed via basic public network.
A COMPREHENSIVE SOLUTION TO CLOUD TRAFFIC TRIBULATIONSijwscjournal
Cloud computing is generally believed to the most gifted technological revolution in computing and it will soon become an industry standard. It is believed that cloud will replace the traditional office setup. However a big question mark exists over the network performance when the cloud traffic explodes. We
call it “explosion” as in future we know that various cloud services replacing desktop computing will be accessed via cloud and the traffic increases exponentially. This journal aims at addressing some of these doubts better called “dangers” about the network performance, when cloud becomes a standard globally and providing a comprehensive solution to those problems. Our study concentrates on, that despite of offering better round-trip times and throughputs, cloud appears to consistently lose large amounts of the data that it is required to send to the clients. In this journal, we give a concise survey on the research efforts in this area. Our survey findings show that the networking research community has converged to the common understanding that a measurement infrastructure is insufficient for the optimal operation and future growth of the cloud. Despite many proposals on building an network measurement infrastructure from the research community, we believe that it will not be in the near future for such an
infrastructure to be fully deployed and operational, due to both the scale and the complexity of the network. We also suggest a set of technologies to identify and manage cloud traffic using IP header DS field, QoS protocols, MPLS/IP Header Compression, Use of high speed edge routers and cloud traffic flow measurement. In the solution DS Field of IP header will be used to recognize the cloud traffic separately, QOS protocols provide the cloud traffic, the type of QOS it requires by allocating resources and marking cloud traffic identification. Further the MPLS/IP Header Compression is performed so that the traffic can pass through the existing network efficiently and speedily. The solution also suggests deployment of high speed edge routers to improve network conditions and finally it suggest to measure the traffic flow using meters for better cloud network management. Our solutions assume that cloud is being assessed via basic public network.
A COMPREHENSIVE SOLUTION TO CLOUD TRAFFIC TRIBULATIONSijwscjournal
Cloud computing is generally believed to the most gifted technological revolution in computing and it
will soon become an industry standard. It is believed that cloud will replace the traditional office setup.
However a big question mark exists over the network performance when the cloud traffic explodes. We
call it “explosion” as in future we know that various cloud services replacing desktop computing will be
accessed via cloud and the traffic increases exponentially. This journal aims at addressing some of these
doubts better called “dangers” about the network performance, when cloud becomes a standard globally
and providing a comprehensive solution to those problems. Our study concentrates on, that despite of
offering better round-trip times and throughputs, cloud appears to consistently lose large amounts of the
data that it is required to send to the clients. In this journal, we give a concise survey on the research
efforts in this area. Our survey findings show that the networking research community has converged to
the common understanding that a measurement infrastructure is insufficient for the optimal operation
and future growth of the cloud. Despite many proposals on building an network measurement
infrastructure from the research community, we believe that it will not be in the near future for such an
infrastructure to be fully deployed and operational, due to both the scale and the complexity of the
network. We also suggest a set of technologies to identify and manage cloud traffic using IP header DS
field, QoS protocols, MPLS/IP Header Compression, Use of high speed edge routers and cloud traffic
flow measurement. In the solution DS Field of IP header will be used to recognize the cloud traffic
separately, QOS protocols provide the cloud traffic, the type of QOS it requires by allocating resources
and marking cloud traffic identification. Further the MPLS/IP Header Compression is performed so that
the traffic can pass through the existing network efficiently and speedily. The solution also suggests
deployment of high speed edge routers to improve network conditions and finally it suggest to measure
the traffic flow using meters for better cloud network management. Our solutions assume that cloud is
being assessed via basic public network.
A COMPREHENSIVE SOLUTION TO CLOUD TRAFFIC TRIBULATIONSijwscjournal
Cloud computing is generally believed to the most gifted technological revolution in computing and it will soon become an industry standard. It is believed that cloud will replace the traditional office setup. However a big question mark exists over the network performance when the cloud traffic explodes. We
call it “explosion” as in future we know that various cloud services replacing desktop computing will be accessed via cloud and the traffic increases exponentially. This journal aims at addressing some of these doubts better called “dangers” about the network performance, when cloud becomes a standard globally and providing a comprehensive solution to those problems. Our study concentrates on, that despite of offering better round-trip times and throughputs, cloud appears to consistently lose large amounts of the data that it is required to send to the clients. In this journal, we give a concise survey on the research efforts in this area. Our survey findings show that the networking research community has converged to the common understanding that a measurement infrastructure is insufficient for the optimal operation and future growth of the cloud. Despite many proposals on building an network measurement infrastructure from the research community, we believe that it will not be in the near future for such an
infrastructure to be fully deployed and operational, due to both the scale and the complexity of the network. We also suggest a set of technologies to identify and manage cloud traffic using IP header DS field, QoS protocols, MPLS/IP Header Compression, Use of high speed edge routers and cloud traffic flow measurement. In the solution DS Field of IP header will be used to recognize the cloud traffic separately, QOS protocols provide the cloud traffic, the type of QOS it requires by allocating resources and marking cloud traffic identification. Further the MPLS/IP Header Compression is performed so that the traffic can pass through the existing network efficiently and speedily. The solution also suggests deployment of high speed edge routers to improve network conditions and finally it suggest to measure the traffic flow using meters for better cloud network management. Our solutions assume that cloud is being assessed via basic public network.
NON-INTRUSIVE REMOTE MONITORING OF SERVICES IN A DATA CENTREcscpconf
Non-intrusive remote monitoring of data centre services should be such that it does not require
(or minimal) modification of legacy code and standard practices. Also, allowing third party
agent to sit on every server in a data centre is a risk from security perspective. Hence, use of
standard such as SNMPv3 is advocated in this kind of environment. There are many tools (open
source or commercial) available which uses SNMP; but we observe that most of the tools do not
have an essential feature for auto-discovery of network. In this paper we present an algorithm
for remote monitoring of services in a data centre. The algorithm has two stages: 1) auto
discovery of network topology and 2) data collection from remote machine. Further, we
compare SNMP with WBEM and identify some other options for remote monitoring of services
and their advantages and disadvantages.
THE DEVELOPMENT AND STUDY OF THE METHODS AND ALGORITHMS FOR THE CLASSIFICATIO...IJCNCJournal
This paper represents the results of the research, which have allowed us to develop a hybrid
approach to the processing, classification, and control of traffic routes. The approach enables to
identify traffic flows in the virtual data center in real-time systems. Our solution is based on the
methods of data mining and machine learning, which enable to classify traffic more accurately
according to more criteria and parameters. As a practical result, the paper represents the
algorithmic solution of the classification of the traffic flows of cloud applications and services
embodied in a module for the controller of the software-defined network. This solution enables to
increase the efficiency of handling user requests to cloud applications and reduce the response
time, which has a positive effect on the quality of service in the network of the virtual data center
A distributed system can be viewed as an environment in which, number of computers/nodes are connected and resources are shared among these computers/nodes. But unfortunately, distributed systems often face the problem of traffic, which can degrade the performance of the system. Traffic management is used to improve scalability and overall system throughput in distributed systems using Software Defined Network (SDN) based systems. Traffic management improves system performance by dividing the work traffic effectively among the participating computers/nodes. Many algorithms were proposed for traffic management and their performance is measured based on certain parameters such as response time, resource utilization, and fault tolerance. Traffic management algorithms are broadly classified into two categories- scheduling and machine learning traffic management. This work presents the study of performance analysis of traffic management algorithms. This analysis can further help in the design of new algorithms. However, when multiple servers are assigned to compile the mysterious code, different kinds of techniques are used. One common example is traffic management. The processes are managed based on power efficiency, networking bandwidth, Processor speed. The desired output will again send back to the developer. If multiple programs have to be compiled then appropriate technique such as scheduling algorithm is used. So the compilation process becomes faster and also the other process can get a chance to compile. SDN based clustering algorithm based on Simulated Annealing whose main goal is to increase network lifetime while maintaining adequate sensing coverage in scenarios where sensor nodes produce uniform or non-uniform data traffic.
A novel token based approach towards packet loss controleSAT Journals
Abstract Due to the advent of technologies like Web 2.0, the Internet applications are able to support transmission of multimedia content to end users. In such applications the transmission might result in packet loss as well. In this context, it is essential to have packet loss control mechanisms that can avoid deterioration of quality of services while rendering media rich content. The quality of service in this case depends on congestion control. Many protocols have been introduced in order to supplement the standard TCP protocol in order to control network congestion. The CSFQ which was built for fair service with open – loop controller has started deterioration in quality as P2P flows dominated Internet traffic of late. One of the closed loop congestion control known as Token-Based Congestion Control (TBCC) was able to restrict consuming resources and provide best service to end users. It monitors inter-domain traffic for trust relationships. Recently, Shi et al. presented a new mechanism known as Stable Token-Limited Congestion Control (STLCC) for controlling inter-domain congestion and improve network performance. In this paper we implement the STLCC mechanism. We built a prototype application that demonstrates the proof of concept. The experimental results revealed that the proposed application is able to control network congestion by controlling packet loss thus improving performance of network. Keywords – Networking, packet loss control, data gram, packet, TCP, congestion control
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A distributed system in its most simplest definition is a group of computers working together as to
appear as a single computer to the end-user. These machines have a shared state, operate
concurrently and can fail independently without affecting the whole system’s uptime.
This is in line with ever-growing technological expansion of the world, distributed systems are
becoming more and more widespread. Take a look at the increasing number of available
computer technologies/innovation around, this is sporadically increasing, and this result in
intense computational requirement.
Yeah, Moore’s law proposed more computing power by fitting more transistors (which
approximately doubles every two years) into a simple chip using cost-efficient approach - cool,
but over the past 5 years, there has been little deviation from this - ability to scale horizontally
and not just vertically alone.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Cloud network management model a novel approach to manage cloud traffic
1. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
CLOUD NETWORK MANAGEMENT MODEL - A
NOVEL APPROACH TO MANAGE CLOUD TRAFFIC
Dr. Mamta Madan1 and Mohit Mathur2
1Professor
Department of Computer Science
Vivekananda Institute of Professional Studies,
(Affiliated to Guru Gobind Singh Indraprastha University), Delhi, India
2Assisstant Professor
Department of Information Technology
Jagan Institute of Management Studies,
(Affiliated to Guru Gobind Singh Indraprastha University), Delhi, India
ABSTRACT
Cloud is in the air. More and More companies and personals are connecting to cloud with so many variety
of offering provided by the companies. The cloud services are based on Internet i.e. TCP/IP. The paper
discusses limitations of one of the main existing network management protocol i.e. Simple Network
Management Protocol (SNMP) with respect to the current network conditions. The network traffic is
growing at a high speed. When we talk about the networked environment of cloud, the monitoring tool
should be capable of handling the traffic tribulations efficiently and represent a correct scenario of the
network condition. The proposed Model ‘Cloud Network Management Model (CNMM)’ provides a
comprehensive solution to manage the growing traffic in cloud and trying to improve communication of
manager and agents as in SNMP (the traditional TCP/IP network management protocol). Firstly CNMM
concentrates on reduction of packet exchange between manager and agent. Secondly it eliminates the
counter problems exist in SNMP by having periodic updates from agent without querying by the manager.
For better management we are including managers using virtualized technology. CNMM is a proposed
model with efficient communication, secure packet delivery and reduced traffic. Though the proposed
model supposed to manage the cloud traffic in a better and efficient way, the model is still a theoretical
study, its implementation and results are yet to discover. The model however is the first step towards
development of supported algorithms and protocol. Our further study will concentrate on development of
supported algorithms.
KEYWORDS
Cloud Computing, Virtualization, SNMP, Network Management, traffic, packets, manager, agent, TCP/IP,
jitter.
1. INTRODUCTION
The Internet is growing by providing lots of online services like search engines, banking, social
networking, gaming and video conferencing across multiple locations. In recent years, large
investments have been made in massive data centers supporting computing services, by Cloud
Service Providers (CSPs) such as Face book, Google, Microsoft, and Yahoo! [8]. The significant
investment in capital outlay by these companies represents an ongoing trend of moving
DOI : 10.5121/ijccsa.2014.4502 9
2. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October
applications, e.g., for desktops or resource
2014
resource-constrained devices like smart phones, into the cloud.
Cloud is on the hype. It is expanding day by day, but
discussed from a technical point
and migration to cloud .Moreover the migration to cloud is due to
to handle higher traffic loads. These d
centers have increased performance, higher capacity and
from Cisco Systems, Global clou
to grow 4.5-fold – a 35% combined annual growth rate.
beyond data centers is increasing rapidly. [1]
centers till 2017. [1]
has not been
point. The cloud traffic growth is a consequence of the fast adoption
Thus data
cloud (Compound Annual Growth Rate, CAGR) traffic is expected
the extent of this growth
data centers use virtualization and automation.
great throughput. According to reports
The traffic between the data centers and
Figure 1 shows the growing traffic statistics in data
3. Figure 1 Data Center Traffic Growths
the ability of cloud data centers
Networking capabilities plays a crucial role for getting data from and storing data to the cloud.
The networking capabilities include
networking devices, bandwidth, protocols etc.
carries several types of traffic. Growing Internet and Cloud are major contributors to this traffic.
The Internet community and researchers are making their best effort to reduce or optimize the
traffic conditions. Though netwo
speed networking devices, there still needs some methods to reduce
traffic on the cloud. The problem lies with the protocols. The traditiona
being able to cop up with the level of services that cloud requires.
cloud it may pass through several components
transfer application, network stack, software VPN, software firewalls and filters, network drivers,
and the hardware network adapter, Network Devices such as Routers, and Gateways
adds its jitter in processing the packet.
Internet Community has already developed so many protocols like
Switching (MPLS), Resource Reservation Protocol (
packets with required quality of s
bitterly manage the network traffic.
protocol Simple Network Management
study, we identified SNMP as one of the protocols whose communication can be optimized
faster and better cloud network;
extent.
Internet
fic networking companies are tiring with development of extremely high
, or efficiently manage
traditional TCP/IP protocols
the
l are not
When a packet travels on the
before it ever leaves the system: system
buffer,
Gateways. Each device
Hence there is very less scope in making delivery fast. The
ternet Multi Protocol Label
RSVP) etc that will help in timely delivery of
services. In our study we are concentrated on how to reduce
ervices. and
For that we surveyed the basic Network management
Protocol (SNMP) which is widely adopted.
During the
for
moreover the traffic generated by SNMP can be reduced to some
For better Quality of Services (QOS)
the current status of the networking devices called
usage etc. Currently, SNMP has been widely used in remote monitoring of network devices and
hosts. In this paper, we would like to discuss the
QOS), system/network administrators should be always aware of
agents, including their CPU loads, storage
s weakness of SNMP in management
10
4. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
communication as well as we will introduce a new Model that will try to overcome those
problems. Management usually requires the support of an agent in the managed host, and the
database in the agent provides the management information needed for a management
application. Let us first enumerate the problems that lie with traditional SNMP protocol.
11
2. PROBLEMS WITH SNMP
In SNMP we know that the Network Management Station (NMS) called manager periodically
requests or polls the agent. The MIB inside agents contains a counter that counts number of bytes
transmitted and received in a particular time interval on each of its interfaces. The counter is
cyclic. The SNMP counters counts only a running total and not the count the number of packets
per interval. SNMP manager send polls to agent to compute packets per interval in short duration
of time. SNMP polls after every five minutes. Thus SNMP poller periodically records these
counters and collects information.[6]
SNMP data collected by polling has many known limitations.
• SNMP uses unreliable User Datagram Protocol (UDP) transport, Data may be lost in
transit .
• Sometimes an SNMP poller restarts and it loses its track of a counter, counter resets (say
after a router reboot), which results in large error in the estimate of traffic. In early
versions of SNMP 32-bit counters were used and these counters reset quickly on high
speed links. Sometimes SNMP poller wrongly calculates the average rate as per
information received, ignoring the missing polls. [12]
• “Jitter” caused by polling is another problem in SNMP. The Network Management
Station must perform polls to many devices and these polls cannot be performed
concurrently. These query –reply packets take some time to transit the network
[9].Finally the result is that the reply packets reach late due to this jitter. Moreover
routers give low priority to SNMP packets; therefore they have a delayed response.
• SNMP processes on agents are given low-priority and hence they have a delayed
response;
• SNMP is too periodic. Sometimes polling cycles from 30 seconds to several minutes long
does not produce the actual picture of the network routing conditions. Even if we speed
up the polling cycle it would miss many routing state changes, and would generate much
management traffic overhead[12].
• SNMP communication delays the action to be taken by manager, as manager has to first
send a query message in which it has to access the MIB , the object data then travel all
the way to manager and if required send the update message to manager. Thus using
SNMP is not meant for very large networks because sending a packet to get another
packet causes delay in communication and hence in management. This type of polling
causes large volumes of regular messages and end in problem response times that may be
unacceptable [7].
• There is no acknowledgement for Trap messages in SNMP. If UDP is used with Internet
Protocol (IP) to deliver trap message by agent, the agent gets no response whether the
trap message has been delivered to manager or not. This is unacceptable for such critical
messages.
• SNMP does not directly support crucial commands. The only way to prompt an event at
an agent is indirectly by setting an object value. A more efficient way is to use remote
procedure calls with parameters, conditions, status and results, that SNMP does not
support.
5. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
• SNMP marginal errors should not be ignored as feeding such small errors into
management process causes major problems, corrupting the results and leads to poor
management.
3. Cloud Network Management Model (CNMM)-A Novel Approach
12
to Manage Cloud Traffic
The Model is based on the agent manager relationship.
3.1 Entities involved in the CNMM
• Virtualized Network Management Server (Manager): is used to manage and supervise the
entire network. It receives all the information and displays it. It may be a pool of
virtualized servers. We can take cloud services for Obtaining Manager Services. We
assume that Manager is virtualized pool of servers kept on cloud. The Manager is usually
in listening mode to have updates from the agents [2].
• The Network Management Agent (Agent): A network node that contains a CNMM agent.
These agents collect and store management information. The agent then creates the
required information send update to Manger. Managed devices (Agents), sometimes
called network elements, are mostly routers having special software installed in them.
They keep the information in the database having collective information from there
routing tables regularly updated through routing protocols and regularly send the updates
to the manager [3]. While implementing CNMM two important points need to be
considered regarding agents. Firstly, we know that the agents are usually routers and
routers are busy with high traffic. The implementations of CNMM will further affect the
performance of router i.e the implementation of CNMM requires generating update
packets and sending updates at regular interval which in turn make router processor busy.
The solution to this problem is that the model suggests sending updates at regular but
large intervals and if the situation is unmanageable within that interval the agent forwards
a trap message. The large interval here depends on the implementation of model.
Moreover we should remember that the model saves the processing overhead required for
query packets that SNMP generates. Secondly, as we know that the management traffic
given lower priority over user data traffic such as voice, chat etc, to solve the problem the
model provide options to prioritize CNMM traffic The prioritization of CNMM traffic
will be discussed in our future work.
• Management information base (MIBs). The agent keeps information in Management
information base (MIB). This information is a collection of objects or data values. Here
each agent will keep the management information about number of packets sent /
received. The SNMP agent process prepares this information from the raw data collected
by it about number of bytes sent/ received [14]. It sends the update packets by extracting
information from MIB. Hence here we are eliminating the problem of actual data
required by manager i.e. number of packets sent/ received. Moreover our MIB is
motivated from the routing table kept by agent. The agent uses this dynamic routing
information from routing table to prepare network condition summary and packet
information in form of packets sent and received from bytes sent/ received. This will
represent the real picture of the network condition to the manager.
3.2 Working of CNMM
The overall working involves a set of agents sending updates about their performance to
managers in the cloud. The updates will be sending only when the value of any parameter of an
6. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
agent goes below its threshold level or when timer expires. However a manager may also send a
query packet if it does not listen from agent for a long time .Whenever an agent sends an update
packet to manager any of the virtualized manager machines reply by checking all parameters. The
benefit of virtualized manager machine is that we are making an efficient use of manager
machines. Moreover since a large number of agents will send their update in short period of time,
it will be difficult to handle them by a single (Non Virtualized) machine. Now if we look at the
information contained in update packet will be the number of packets sent/received instead of
number of bytes sent/ received in a particular interval of time. Each agent keeps its performance
or other information in a set of objects called Management Information Base (MIB). The manager
has rights to access/modify these MIB’s. Though each time to access the Agents MIB manager
has to authenticate and show access rights to the agent. Usually agent will take initiative by
sending the update message to manager but manager may need to access MIB while responding
to these updates to modify the object values. The initiative taken by agent to update manager will
reduce the unnecessary traffic created by SNMP in Query and reply packets. This will also
eliminate polling problems that lies in SNMP. Moreover it will reduce the time of overall
communication and further eliminate the problems related to counters and jitter.
For better QoS of cloud services, system/network administrators of network should also be
always aware of the current status of the manager machines in the cluster, including their CPU
loads, storage usage, and network utilization. Furthermore, administrators are also interested in
how many Virtual Machine (VM) instances are allocated in a manager host machine and how
well each VM instance is running. As a great number of managers that are deployed to provide
virtual machines to a variety of agents. The Model is a hybrid of centralized and decentralized
management. The basis of suggested Model lies in the initiative taken during the communication.
The initiative to transfer is taken by agent instead of manager. The manager will not generate any
request messages as in SNMP. The agent keeps database of information such as MIB and send
updates of its database to its manager. Some information might relate to the system, some might
be network related, some might be resource specific and there will be events associated with each
incident [10]. The updates are sent similarly as in link state protocol of routing i.e. the agent send
an update whenever the value of any object goes below its threshold. Each object in the database
has been defined with a threshold value. The value below that threshold will not be tolerated and
immediately informed to the manager to take action. The communication will be initiated by
agent instead of manager. For proper management, all the messages in CNMM are
acknowledged.
13
3.3 Types of Messages
CNMM defines the following basic types of packets:
• Regular Update Packet( From Agent To Manager)
• Trap Message(from Agent to Manager, in case of urgent action)
• Action/ Set Message(Reply Message From manager to Agent)
• Get Message(From Manager to agent in case manager does not hear from agent for a long
time)
• Advertisement Message (By new Agent that enters a network to Manager.)
• Registration Message(By Manager to agent after receiving advertisement)
7. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October
3.3.1 Regular Update Packet
Action/ Set Message
Figure 2 A simple example of
CNMM communication
The Figure 2 shows how update message is communicated between agents and pool of virtualized
manager. Agent gent keeps its performance value
(Packet sent/ received and other related information)
as set of object in a database; the values will be updated regularly as per pe
agent. The values will be monitored by the
minimum threshold value below which it cannot be tolerated. Moreover a value called minimum
value which is above threshold level is also
performance parameters of agent. This means that an agent will keep multiple values of its
performance in its database. The messages are generated by agent whenever the performance
value of any parameter of agent re
described later. Such messages are then forwarded to the respective
This means that manager can assume that everything is going well if it does not get any packet
from a manager up to a period of time. For this
expires the manager sends get message
More over it may happen that the value of the agent performance may reach below threshold
level. In this case the agent generates an alert message. The manager then takes care of such
messages by read or writes instructions/ messages sent to agent.
which update and alert messages were sent to the manager by agent. Manager has all rights to
update or edit or access the values inside agent database but it has to authenticate itself before
messages are accepted by to agent database. Our
avoiding the query packets generated by SNMP managers.
20. Figure 3 Agents Performance levels in
performance of the
program inside the agent itself and compared with the
defined. These values are defined for various
reaches minimum level or before the expiration of update timer
manager to take some action.
ger manager keeps a timer for each agent. If the
the agent to check whether everything is fine.
Figure 3 shows the levels at
Model reduces the management
CNMM
24. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
15
3.3.2 Trap Reply Message
An Agent can also send a trap message in case of emergency i.e. when it requires an immediate
action from manager without delay. The manager in that case will process the request with
highest priority. Figure4 shows exchange of trap and trap reply message. The messages are
generated by agent whenever the performance value of any parameter of agent reaches threshold
message.
Figure 4 Trap Reply Message
3.3.3Advertisement and Registration
25. CNMM also support advertisement and the registration. Whenever a new host enters the network
it first of all discovers its NMS and then send an advertisement message to the NMS about its
existence in the network. The NMS then registers the host. The extension of this capability is to
extend the same to a broader cloud scenario without compromising the functioning and overhead.
Figure 5 shows the exchange of advertisement and registration message.
Figure 5 Advertisement Registration Message
3.4 CNMM Timers
Update Timer
26. For a proper management, Manager keeps timers. Manager keeps an update timer which starts
when manager receives an update message from agent. The agent is expected to send an update
before expiration of this timer. When the timer expires the manager sends a get message to get the
status of agent. If the agent replies, all goes well otherwise another get message is sent. This is
repeated three times after which the manager alerts the management console about the event to
take some action.
3.5 Virtualized Manager
Next the Model suggests that we may have a pool of managers that work for a set of agents. But
these managers are using virtualization technology. A physical manager is converted into
27. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October
multiple virtual machines using virtualization technology.
physical device, capable of running its own
focus on how this virtualization technology works and will also highlight manager to manager
communication, packet formats etc.
like increase utilization of infrastructure,
recovery time reduction, fast deployment of
operating costs.[13] Virtualization is realized by introducing a virtualization layer between
hardware and the operating system.
Virtual Machine Monitor (VMM)
systems, and allows their shared access to the real hardware resources, including CPU, memory,
and I/O devices. Further we can insert a thin layer of software (hypervisor) between the server
hardware and the operating system
applications and operating systems [
inside virtualized managers. [13]
%(
)$
* +
31. ,,,
Use of hypervisor imposes the many benefits
have, like Isolation, Multiplicity, Abstraction and Encapsulation.
3.6 CNMM Security
like a unique
We know that SNMP v3 uses User security
USM is that USM utilizes a separate user and key
user and key management infrastructure introduces significant operational costs
architecture was not designed with
ASIs between the subsystems do not pass all the necessary security information to all subsystems.
If we look at the other security solutions for SNMP
protocols such as Secure Shell(
Layer security(DTLS). These protocols have an already
and key management for these protocols
models have in common that they
on a per session basis, called session
Each virtual manager acts l
33. (OS). [13] Our future work will
Making use of Virtualized Manager carries several benefits
fast replying time to agents, application downtime and
applications and reducing infrastructure and
ization The virtualization layer, realized by a VM hypervisor or
VMM), enables the creation of virtual machines in different operating
system. The hypervisor contains virtual hardware containers
13]. Figure 6 shows the various layers of communication
pools of Virtualized Managers in the Cloud
on virtual managers that traditional managers do not
, [13]
model (USM). The main reason of not deploying
management infrastructure. Deploying another
[4]
session based security in mind. As a consequence, the original
that leverage existing secure transport
SSH), Transport Layer Security(TLS) and Datagram Transport
. widely deployed security infrastructure
is generally well understood. These all secure transport
use a concept of a session and provide security services
session-based security. By providing security services
2014
16
alized , l that host
. s eploying 4]. The SNMP
based
at the
34. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
transport layer instead of embedding security services into the SNMP protocol itself, the usability
in operational environments can be significantly improved.
However using SSH/TLS/DTLS require session establishment, however we are more concerned
about the speed of communication as well as achieving basic security [15]. Session establishment
and other sophistication required by these protocols causes delays, hence we concentrate only on
providing authentication, confidentiality and integrity and access control to the CNMM packets.
We do not suggest any establishment of session as it will cause delay to overall communication.
We used a hybrid approach to achieve complete security. The CNMM security includes Securing
(providing confidentiality and Authentication) to the packets that are being exchanged between
Agent and manager.
The CNMM secure packet exchange involves authentication, confidentiality and message
integrity.
The purpose of the CNMM secure packet exchange involves taking an application message to be
transmitted, fragmenting it, encapsulating it with appropriate headers, and finally encrypting it
before it is forwarded using UDP protocol.
17
The steps involved in creating a secure packet are as follows:
Step 1 First of all a header is added to the application data portion. A header keeps information
such as data size and the MAC. The data is then classified into packets.
Step 2 Packets are then compressed, so that it will be reduced to contain less byte.
Step 3 The data is then encrypted using encryption techniques. To provide authentication code
called message authentication Code (MAC) is calculated and placed in the header. A secret key
is created during creation of MAC, this key is either a client chosen MAC secret or a server
chosen MAC secret respectively, and it depends on which party prepares the packet.
!
# # $ # %
!
#
' !#
!
Figure 7 CNMM Application Data Processing for security
35. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
Step 4 Next, the data plus the MAC are encrypted using a previously agreed upon symmetric
encryption algorithm, for example Data Encryption Standard (DES), triple DES, International
data Encryption Algorithm (IDEA), Blowfish etc. Both data and MAC are encrypted.
Step 5 Encrypted Data packet and MAC together makes a secure packet as it is ready to move to
the insecure public network.
The whole procedure provides confidentiality, authentication, Integrity and compression to the
CNMM communication [5].The whole procedure is illustrated in Figure 7.
18
3.7 Benefits of the Proposed Model
1. Help enhance network performance and lower risk- Since packets are initiated by CNMM
Agent, The polling done in SNMP can be avoided. Less number of packets led to less
jitter and hence enhances network performance.
2. Reduce network Traffic- The polling packets in SNMP are not used in CNMM as well as
agent too generates a packet only when it is required, this reduces the unnecessary query
and response messages generated in SNMP.
3. Secure Communication between Managers and Agents- CNMM packets use secure and
authenticated packets which provides confidentiality, authentication and Message
Integrity to each packet communicated.
4. Better Communication and updated information with managers- Managers are still
updated, though we have less packet exchange. The updates sent by agent are kept in
manager’s database.
5. Faster recovery in case of failures- since we are using the concept of manager
virtualization the recovery to failures is very fast.
6. Virtualization benefits- All benefits that come under virtualization technology were
achieved in CNMM Manager.
7. No Polling Problems- All the problems related to Polling in SNMP will be solved as no
polling is done by manager to gather information / status of CNMM Agent.
8. More Accurate Change Management and Planning Processes: Since CNMM’s agent MIB
is motivated with the Routing Table information; it calculates and the change in routing
and traffic based on the traffic and routing matrix which is more close to the actual
network scenario. The new traffic and routing picture and its analysis show whether any
congestion will result or not. [11]
4. CONCLUSION
Cloud computing is an emerging technology. More and More individuals and companies are
adopting cloud at a faster rate, due to which internet traffic is increasing at a pace which is
difficult to manage. With development of new technologies in the cloud we need to modify the
traditional protocols to manage the increasing cloud traffic. Cloud Network Management Model
is such a Model that efficiently manages cloud traffic with more accurate results and providing
security to the management packets being exchanged. Though, the paper describes the Cloud
Network Management Model at abstract level. Our future research work will concentrate on
describing each part of the Model at detailed design and at implementation level. In continuation
we will focus on analyzing the use of OpenFlow to check the flows of traffic in cloud and then
take some decisions on to which network manager to forward the messages to.
36. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
19
ACKNOWLEDGMENT
First of all we would like to acknowledge Goddess Saraswati for making us capable of writing
this research paper. Further, we would like to thank everyone at workplace and anonymous
reviewers for their useful comments and suggestions.
REFERENCES
[1] White Paper ,“Cisco Global Cloud Index: Forecast and Methodology, 2012–2017”,Cisco ,October
2013.
[2] Ya-shiang peng, Yen-cheng Chen “SNMP-based monitoring of heterogeneous virtual infrastructure in
clouds”
[3] J. Swarna, C. Senthil raja, Dr.K.S.ravichandran ,“Cloud monitoring based on snmp”.
[4] Jürgen schönwälder, , and Vladislav marinov, “On the impact of security protocols on the
performance of snmp”, IEEE transactions on network and service management, vol. 8, no. 1, march
2011.
[5] Ricardo Hillbrecht, Luis Carlos e. De bona ,“A SNMP-based virtual machines management
interface”, IEEE/ACM fifth international conference on utility and cloud computing, 2012.
[6] Laurent Andrey, Olivier Festor, Abdelkader Lahmadi, Aiko pras and Jürgen Schönwälder, “Survey of
snmp performance analysis studies”, international journal of network management,int. J. Network
mgmt , 19: 527–54, 2009.
[7] Jens Rupp “Quo vadis, snmp?”-White paper, Paessler A.G, august 2010 – last update: july 2011.
[8] Joe Wenjie Jiang, “Wide-area traffic management for cloud services”, a dissertation presented to the
faculty of princeton university in candidacy for the degree of doctor of philosophy.
[9] Barford p, sommers j, “Comparing probe- and router-based packet-loss measurement.” IEEE internet
computing magazine 2004; 8(5): 50–56.
[10] A. Bianco, r. Birke, f. Debele, and l. Giraudo, “snmp management in a distributed software router
architecture,”, IEEE Intl. Conference on communications (icc’11), pp. 1–5, jun. 2011.
[11] “Managing the Cloud in Cloud Computing with Route Analytics Packet design”, 2009, Corporate
Headquarters, Packet Design Inc., 2455 Augustine Drive, Santa Clara, CA 95054.
[12] Matthew Roughan, “A Case Study of the Accuracy of SNMP Measurements”, Australia, Journal of
Electrical and Computer Engineering Volume 2010, Article ID 812979, 7 pages
[13] White paper, Server Virtualization: Branching Out of the Data Center, by Cisco, 2011
[14] White Paper, Managing IP Network Unpredictability with Route Analytics, by Packet Design, 2008.
[15] Tomasz Onyszko, Secure Socket Layer, Article Published on 19 July 2002,
http://www.windowsecurity.com/articles-tutorials/
authentication_and_encryption/Secure_Socket_Layer.html
Authors
Dr Mamta Madan
Professor Mamta Madan is an accomplished professor of Computer Science at VIPS, IP University. She
has over 17 years of experience in research and academics. She is actively involved in research in the areas
of artificial intelligence, software engineering, data mining and cloud computing. She is guiding many
Ph.D students enrolled at various Indian universities. She is associated with many professional and research
bodies like Central Board of Secondary Education, Computer Society of India etc. Her expertise goes well
beyond the classroom, as she is in the panel of examiners at various universities and has evaluated
numerous projects of computer science. She has published and presented many papers in National and
International Journals of repute.
37. International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 5, October 2014
20
Mr. Mohit Mathur
Mohit Mathur is working as Head of Department, Dept. of Information Technology at Jagan Institute of
Management Studies, Delhi, India. He has done his Graduation of Delhi University and MCA from
Department of Electronics, Ministry of Information Technology, India. His area of Interest is Network /
Network security. He is pursuing his Research work on Cloud Computing. He has already written many
research papers in the same area representing different aspects of cloud like security, traffic, scalability,
migration etc.