이기종 무선 환경에서 Load sharing을 이용한 Soft Load Balancing 기술

손혁민(Hyukmin Son),이상훈(Sanghoon Lee),김수창(Soochang Kim),신연승(Yeonseung Shin) 한국통신학회 2008 韓國通信學會論文誌 Vol.33 No.7A

차세대 이동 통신망의 발전으로 상용 망과 이 기종 망이 서로 겹쳐진 다중 망 구조가 형성될 것이다. 이러한 여러 망이 겹쳐진 다중 망 구조에서 전체 무선자원의 사용 효율을 높이고 Eb/Io (bit energy-to-interference plus noise density ratio)를 개선하기 위해 이기종망간 혹은 동종망간 상호 연동 기술이 필요하다. 본 논문에서는 이러한 동종망과 이기종망들이 서로 겹쳐져있는 다중 셀 환경에서 load를 효율적으로 분산 시킴으로써 무선 자원의 효율을 높이고 신호의 간섭양을 줄여 사용자의 QoS 보장 및 성능 개선을 위한 soft load balancing algorithm을 제안 및 분석한다. 본 논문에서는 수학적 분석을 통해 효율적인 load sharing을 위한 최적의 LBR (load balancing ratio) 을 구하고 이를 이용하여 각 network에 traffic 양을 할당하여 서비스 한다. 그러므로 soft load balancing 알고리듬은 보다 안정적인 데이터 전송을 가능하게 한다. Start Ongoing next generation networks are expected to be deployed over current existing networks, in the form of overlayed heterogeneous networks, in particular, in hot spot areas. Therefore, it will be necessary to develop an interworking technique such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load balancing mechanism termed 'soft' load balancing where the IP (Internet Protocol) traffic of a user is divided into sub-traffic, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load sharing and handover techniques. Through a numerical analysis, we obtain an optimal LBR (Load Balancing Ratio) for determining the volume of traffic delivered to each network over an overlayed multi-cell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by reducing the outage probability efficiently for a given user traffic.

Effort of Load Balancer to Achieve Green Cloud Computing : A Review

G.Siva Shanmugam,N.Ch.S. N. Iyengar 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.3

In a distributed system, from the starting days onwards distribution of load among servers becomes a serious problem in the commercial Internet. The problem in this scenario is? The entire single application oriented server has to engage the entire amount of traffic and if they went down, all commercial activities come down offline result out of business. Running individually the application server couldn’t support start-up budgets. The folks involved in the Web Commercial plan to solve this problem by distributing the load evenly to all the servers running on the web host owned by different agents or organizations; thus new scenario was born named as Load Balancing. In this treatise, we investigate several shapes attenuated by load Balancer and reviewed the algorithms proposed on load balancing. Here we took both static as well as dynamic based algorithms and their performances are formulated by comparison with all other existing scheme. This paper also brings connectivity on green computing with cloud load balancers. By cloud computing we can attain multi tenancy and dynamic resource handling which automatically reduces co2 emission from servers. Without the facility of sharing single resources among thousands of peoples, green computing is not possible. So the nature of cloud load balancer and green computing was illustrated here.

이기종 무선 환경에서 Load sharing을 이용한 Soft Load Balancing 기술

손혁민,이상훈,김수창,신연승 한국통신학회 2008 韓國通信學會論文誌 Vol.33 No.7

Start Ongoing next generation networks are expected to be deployed over current existing networks, in the form of overlayed heterogeneous networks, in particular, in hot spot areas. Therefore, it will be necessary to develop an interworking technique such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load balancing mechanism termed `soft' load balancing where the IP (Internet Protocol) traffic of a user is divided into sub-traffic, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load sharing and handover techniques. Through a numerical analysis, we obtain an optimal LBR (Load Balancing Ratio) for determining the volume of traffic delivered to each network over an overlayed multi-cell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by reducing the outage probability efficiently for a given user traffic. 차세대 이동 통신망의 발전으로 상용 망과 이 기종 망이 서로 겹쳐진 다중 망 구조가 형성될 것이다. 이러한 여러 망이 겹쳐진 다중 망 구조에서 전체 무선자원의 사용 효율을 높이고 Eb/Io (bit energy-to-interference plus noise density ratio)를 개선하기 위해 이기종망간 혹은 동종망간 상호 연동 기술이 필요하다. 본 논문에서는 이러한 동종망과 이기종망들이 서로 겹쳐져있는 다중 셀 환경에서 load를 효율적으로 분산 시킴으로써 무선 자원의 효율을 높이고 신호의 간섭양을 줄여 사용자의 QoS 보장 및 성능 개선을 위한 soft load balancing algorithm을 제안 및 분석한다. 본 논문에서는 수학적 분석을 통해 효율적인 load sharing을 위한 최적의 LBR (load balancing ratio) 을 구하고 이를 이용하여 각 network에 traffic 양을 할당하여 서비스 한다. 그러므로 soft load balancing 알고리듬은 보다 안정적인 데이터 전송을 가능하게 한다.

무선 인터넷 프록시 서버 클러스터에서 호스트 부하 정보에 기반한 동적 부하 분산 방안

곽후근(Hukeun Kwak),정규식(Kyusik Chung) 한국정보과학회 2006 정보과학회논문지 : 정보통신 Vol.33 No.3

무선 인터넷 프록시 서버 클러스터에서 부하 분산기는 사용자의 요청을 각 서버로 분산시키는 역할을 한다. 리눅스 가상 서버(LVS: Linux Virtual Server)는 소프트웨어적으로 사용되는 부하 분산기로써 여러 가지 스케줄링 방식들을 지원한다. LVS 스케줄링 방식에는 라운드 로빈 방식, 해슁 기반 방식, 또는 서버와 부하 분산기 사이에서 서버로 연결된 커넥션 개수를 이용하는 방식이 있다. 일부 향상된 방법에서는 각 서버별로 서버의 최고 성능 범위 안에서 허용된 커넥션 개수의 상한값과 하한값을 사전에 결정하여 이를 스케줄링 시에 적용한다. 그러나, 이러한 스케줄링 방법들에서는 서버의 실시간 부하 정보들이 부하 분산에 반영되지 않는다. 본 논문에서는 서버 부하 정보에 기반한 동적 스케줄링 방식을 제안한다. 제안된 방식에서는 부하 분산기가 서버의 실시간 CPU 부하 정보를 바탕으로 가장 적은 부하를 가지는 서버에 새로운 요청을 할당한다. 16대로 구성된 클러스터링 컴퓨터와 정적 컨텐츠(이미지와 HTML)를 가지고 실험을 수행하였다. 실험결과 CPU를 많이 사용하는 요청과 호스트의 성능이 다른 경우에 대하여 종래의 스케줄링 방식보다 성능이 향상됨을 확인하였다. A server load balancer is used to accept and distribute client requests to one of servers in a wireless internet proxy server cluster. LVS(Linux Virtual Server), a software based server load balancer, can support several load balancing algorithms where client requests are distributed to servers in a round robin way, in a hashing-based way or in a way to assign first to the server with the least number of its concurrent connections to LVS. An improved load balancing algorithm to consider server performance was proposed where they check upper and lower limits of concurrent connection numbers to be allowed within each maximum server performance in advance and apply the static limits to load balancing. However, they do not apply run-time server load information dynamically to load balancing. In this paper, we propose a dynamic load balancing scheme where the load balancer keeps each server CPU load information at run time and assigns a new client request first to the server with the lowest load. Using a cluster consisting of 16 PCs, we performed experiments with static content(image and HTML). Compared to the existing schemes, experimental results show performance improvement in the cases of client requests requiring CPU-intensive processing and a cluster consisting of servers with difference performance.

A New Fuzzy Logic and GSO based Load balancing Mechanism for Public Cloud

Uma Singhal,Sanjeev Jain 보안공학연구지원센터 2014 International Journal of Grid and Distributed Comp Vol.7 No.5

The recent advances in cloud computing set up well established research in Distributed computing, virtualization, web services, utility computing, have offered many benefits in scalability, cost and efficiency for cloud service users. These advantages are further expected to fulfill the demands of cloud users for cloud services efficiently. This brings the problem of fault tolerance, scalability, efficiency, high availability. Central to these issues require the dynamic and efficient load balancing techniques. In this paper, an effective load balance model is presented for public cloud in which cloud is partitioned with a switch mechanism to choose different load balancing strategy for different load. Fuzzy Logic have been extensively used in various applications such as image processing, data mining, networking, etc. due to its efficient internal architecture and its compatibility to solve various optimization problems. Fuzzy base networks have been observed to produce optimal results in various combinatorial optimization problems. Another important area which provides significant results in solving optimization is the swarm intelligence approach. GSO is observed to have provided significant optimal solution in lesser iterations. In this paper The Fuzzy logic and GSO based load balancing algorithm applied to the load balancing strategy to enhance the utilization and efficiency in the public cloud environment.

분산형 레이어 7 서버 부하 분산

권희웅,곽후근,정규식 한국정보처리학회 2008 정보처리학회논문지. 컴퓨터 및 통신시스템 Vol.15 No.4

A Clustering based wireless internet proxy server needs a layer-7 load balancer with URL hashing methods to reduce the total storage space for servers. Layer-4 load balancer located in front of server cluster is to distribute client requests to the servers with the same contents at transport layer, such as TCP or UDP, without looking at the content of the request. Layer-7 load balancer located in front of server cluster is to parse client requests in application layer and distribute them to servers based on different types of request contents. Layer 7 load balancer allows servers to have different contents in an exclusive way so that it can minimize the total storage space for servers and improve overall cluster performance. However, its scalability is limited due to the high overhead of parsing requests in application layer as different from layer-4 load balancer. In order to overcome its scalability limitation, in this paper, we propose a distributed layer-7 load balancer by replacing a single layer-7 load balancer in the conventional scheme by a single layer-4 load balancer located in front of server cluster and a set of layer-7 load balancers located at server cluster. In a clustering based wireless internet proxy server, we implemented the conventional scheme by using KTCPVS(Kernel TCP Virtual Server), a linux based layer-7 load balancer. Also, we implemented the proposed scheme by using IPVS(IP Virtual Server), a linux-based layer-4 load balancer, installing KTCPVS in each server, and making them work together. We performed experiments using 16 PCs. Experimental results show scalability and high performance of the proposed scheme, as the number of servers grows, compared to the conventional scheme. 무선 인터넷 프록시 서버 클러스터링에서 저장공간을 최소화하기 위해서는 URL 해싱기법을 가진 Layer 7 부하분산기가 필요하다. 서버 클러스터 앞단에 위치한 Layer 4 부하분산기는 TCP 또는 UDP와 같은 트랜스포트 계층에서 컨텐츠 내용을 확인하지 않고 사용자 요청들을 똑같은 컨텐츠를 가진 서버들에게 분배한다. 서버 클러스터 앞단에 위치한 Layer 7 부하분산기는 응용계층에서 사용자 요청을 분석하여 요청 컨텐츠 유형에 따라 해당되는 서버들에게 분배한다. Layer 7 부하분산기를 이용하면 서버들이 배타적으로 각기 다른 컨텐츠를 가지게 할 수 있어서 서버들 저장공간을 최소화할 수 있으며 전체 클러스터 성능을 향상할 수 있다. 그러나 Layer 7 부하분산기는 응용계층에서 사용자 요청을 분석하는데 요구되는 큰 처리 부담으로 인해 Layer 4 부하분산기와 다르게 확장성이 제한된다. 본 논문에서는 그 확장성 제한을 극복하기 위해서 분산형 Layer 7 부하분산기를 제안한다. 종래의 방법에서는 한 대의 Layer 7 부하분산기를 사용하는데 본 논문에서 제안한 방법에서는 서버 클러스터 앞에 한 대의 Layer 4 부하분산기를 설치하고 서버들에게 Layer 7 부하분산기들을 각각 설치한다. 클러스터 기반의 무선 인터넷 프록시 서버에서 종래의 방법을 리눅스기반의 Layer 7 부하분산기인 KTCPVS를 이용하여 구현하였다. 본 논문에서 제안한 방법에서는 리눅스기반의 Layer 4 부하분산기인 IPVS를 사용하고 각 서버들에게 Layer 7 부하분산기인 KTCPVS를 설치하여 같이 동작하게 구현하였다. 실험은 16대의 컴퓨터를 사용하여 수행되었고, 실험 결과에 의하면 제안 방법이 종래 방법에 비해 서버 대수가 증가함에 따라 확장성 및 높은 성능 향상률을 가짐을 확인하였다.

이산시간 2단계 서비스 대기행렬을 이용한 로드밸런싱 프로세스 설계

박현민 ( Hyun Min Park ) 한국생산성학회 2013 生産性論集 Vol.27 No.4

This paper introduces a new load balancing algorithm and a method of estimating the performance of the load balancer in a network composed of a multi-server sharing the entire load such as cloud computing. A load balancer collects newly arrived traffic in batches and distributes the batches sequentially. A discrete-time Geo/G/1 queueing model having a heterogeneous two-phase service mode with a fixed-size batch is applied for designing the optimal load balancing rule. The stationary queue length and regeneration cycle length are derived so that the long-run average cost function of a load balancer could be analyzed. A numerical example also illustrates the process of finding the optimal threshold value that minimizes the work load of a load balancer.

Adaptive Load Balancing Method Enabling Auto-Specifying Threshold of Node Load Status for Apache Flume

UnGyu Han,Jinho Ahn 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.2

Typically, the previous load balancing methods for Flume which completely depends on the user-specified threshold does not adaptively deal with the performance change of the entire log processing system at runtime. Furthermore, their task-transferring algorithm aggravates the performance degradation of the overloaded node because the excessive data transfer to another node should be done on the overloaded node. In this paper, we propose a new load balancing method for Apache Flume by automatically and dynamically modifying threshold of node load status in accordance with the runtime performance of the system. This feature can be realized by monitoring both the increasing rate of incoming log information in the queue of each collector agent and its occupancy rate at the request of the overloaded or under-loaded collection node in a decentralized manner. The proposed method considerably alleviates the additional overhead incurred by the task migration and makes the load of the entire system as fair as possible by selecting the optimal task migration destination depending on the current load-state values of collector agents unlike the previous round-robin and random ones.

Estimation-Based Load-Balancing with Admission Control for Cluster Web Servers

Saeed Sharifian,Seyed Ahmad Motamedi,Mohammad Kazem Akbari 한국전자통신연구원 2009 ETRI Journal Vol.31 No.2

The growth of the World Wide Web and web-based applications is creating demand for high performance web servers to offer better throughput and shorter user-perceived latency. This demand leads to widely used cluster-based web servers in the Internet infrastructure. Load balancing algorithms play an important role in boosting the performance of cluster web servers. Previous load balancing algorithms suffer a significant performance drop under dynamic and database-driven workloads. We propose an estimation-based load balancing algorithm with admission control for cluster-based web servers. Because it is difficult to accurately determine the load of web servers, we propose an approximate policy. The algorithm classifies requests based on their service times and tracks the number of outstanding requests from each class in each web server node to dynamically estimate each web server load state. The available capacity of each web server is then computed and used for the load balancing and admission control decisions. The implementation results confirm that the proposed scheme improves both the mean response time and the throughput of clusters compared to rival load balancing algorithms and prevents clusters being overloaded even when request rates are beyond the cluster capacity.

End-to-end Reliable Message Transmission Considering Load Balancing in Wireless Networks

( Anh Tai Tran ),( Myung Kyun Kim ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.9

This paper proposes a load balanced reliable routing protocol called LBR (Load Balanced Reliable routing) in wireless networks. The LBR protocol transmits messages through a reliable path considering the balancing of the traffic load. Recently, the authors have proposed a multipath-based reliable routing protocol called MRFR, which is an appealing protocol for fault tolerant reliable data transmission. However, However, MRFR has no concern with the problem of load balancing, which results in increasing congestion and consuming high energy at some network nodes. As a result, the problem affects negatively the performance of the network. Taking account of load balancing as a route selection criteria can avoid routing through the congested nodes and allows to find better routes. In this paper, we extend MRFR by considering load balancing in the route discovery process of reliable communication. The simulation results showed that the proposed protocol outperforms AODV in terms of end-to-end delay, packet delivery radio, and average jitter. Compared to MRFR, the LBR protocol has the same packet delivery ratio, and obtains a better efficiency of load balancing.