Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974529
Michele Paolino, J. Fanguede, Nikolay Nikolaev, D. Raho
NFV is more and more leveraging open source as a suitable direction to mitigate traditional vendor lock-in effects. The operators interest and strong involvement in open source communities like OPNFV, OpenStack, OVS and DPDK are in fact continuously growing. However, real deployments are still lacking open source solutions. In this paper, the challenges that NFV open source projects are facing to be deployed in operator production environments are identified. Furthermore, the Virtual Open Systems experience in building VOSYSwitch, a user space virtual switch product based on an open source networking framework (Snabb) is presented together with a set of benchmarks which showcase its carrier grade performance level. In fact, the performance results show that VOSYSwitch outperforms OVS-DPDK, a virtual switch solution used in many real deployment environments, which is also the basis of other virtual switch solutions, such as CuckooSwitch, Ensemble Connector, and VPP (DPDK).
{"title":"Turning an open source project into a carrier grade vswitch for NFV: Vosyswitch challenges & results","authors":"Michele Paolino, J. Fanguede, Nikolay Nikolaev, D. Raho","doi":"10.1109/ICNIDC.2016.7974529","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974529","url":null,"abstract":"NFV is more and more leveraging open source as a suitable direction to mitigate traditional vendor lock-in effects. The operators interest and strong involvement in open source communities like OPNFV, OpenStack, OVS and DPDK are in fact continuously growing. However, real deployments are still lacking open source solutions. In this paper, the challenges that NFV open source projects are facing to be deployed in operator production environments are identified. Furthermore, the Virtual Open Systems experience in building VOSYSwitch, a user space virtual switch product based on an open source networking framework (Snabb) is presented together with a set of benchmarks which showcase its carrier grade performance level. In fact, the performance results show that VOSYSwitch outperforms OVS-DPDK, a virtual switch solution used in many real deployment environments, which is also the basis of other virtual switch solutions, such as CuckooSwitch, Ensemble Connector, and VPP (DPDK).","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127143024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974598
Shu Chen, Guang Chen, Wei Wang
Employing pre-trained word embeddings as preliminary features in convolutional neural networks (CNN) for natural language processing (NLP) tasks has been proved to be of benefit. We exploit this idea by taking advantage of different types of word embeddings at the same time. To be specific, we extend CNN models to coordinate two lookup tables, which exploit semantic word embeddings and syntactic word embeddings at the same time. We test our models on several review datasets and all results indicate the positive effect on sentiment analysis. To understand the reason behind, we explore the difference of the two word embeddings and how they influence the CNN models.
{"title":"The joint effect of semantic and syntactic word embeddings on sentiment analysis","authors":"Shu Chen, Guang Chen, Wei Wang","doi":"10.1109/ICNIDC.2016.7974598","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974598","url":null,"abstract":"Employing pre-trained word embeddings as preliminary features in convolutional neural networks (CNN) for natural language processing (NLP) tasks has been proved to be of benefit. We exploit this idea by taking advantage of different types of word embeddings at the same time. To be specific, we extend CNN models to coordinate two lookup tables, which exploit semantic word embeddings and syntactic word embeddings at the same time. We test our models on several review datasets and all results indicate the positive effect on sentiment analysis. To understand the reason behind, we explore the difference of the two word embeddings and how they influence the CNN models.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125042902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974563
Ling Huang, Songguang Tang, Jiani Hu, Weihong Deng
Saliency detection plays an important role in computer vision. This paper proposes a saliency detection algorithm which is based on multi-cue and multi-scale with cellular automata. The algorithm constructs a background-based map at first and optimizes it with an automatic updating mechanism — single-layer cellular automata. Furthermore, two important visual cues, focusness and objectness, are added to evaluate saliency in different perspectives. In addition, multi-scale is introduced to avoid the saliency results' sensitive to different scales and the output saliency map is generated by multi-layer fusion. Extensive experiments on three public datasets comparing with other state-of-the-art results demonstrate the superior of the algorithm.
{"title":"Saliency detection based on multi-cue and multi-scale with cellular automata","authors":"Ling Huang, Songguang Tang, Jiani Hu, Weihong Deng","doi":"10.1109/ICNIDC.2016.7974563","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974563","url":null,"abstract":"Saliency detection plays an important role in computer vision. This paper proposes a saliency detection algorithm which is based on multi-cue and multi-scale with cellular automata. The algorithm constructs a background-based map at first and optimizes it with an automatic updating mechanism — single-layer cellular automata. Furthermore, two important visual cues, focusness and objectness, are added to evaluate saliency in different perspectives. In addition, multi-scale is introduced to avoid the saliency results' sensitive to different scales and the output saliency map is generated by multi-layer fusion. Extensive experiments on three public datasets comparing with other state-of-the-art results demonstrate the superior of the algorithm.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123238639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974531
Weijia Wang, Xiaofeng Qiu, Li Sun, Rui Zhao
Software-Defined Security (SDS), which provides a flexible and centralized security solution by abstracting the security mechanisms from the hardware layer into a software layer, attracts many researchers to study the detail of this conception. One of the key challenges of SDS is how to schedule and orchestrate security appliances according to huge and heterogeneous threat information, especially when they are still lack of standardized interfaces. In this paper, we present a data driven Security Device Orchestration Framework (SDOF) for SDS. In SDOF, we put forward uniform interfaces for security devices so that they could be orchestrated by software and their data could be collected and processed centrally. The complex Structured Threat Information eXpression (STIX) ontology and corresponding tools are tailored for SDOF to standardize and centralize all data in SDS. These two achievements makes real-time dynamic orchestration possible in SDS. We also provide an orchestration scenario to demonstrate how SDOF works and evaluated its performance.
{"title":"A data driven orchestration framework in software defined security","authors":"Weijia Wang, Xiaofeng Qiu, Li Sun, Rui Zhao","doi":"10.1109/ICNIDC.2016.7974531","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974531","url":null,"abstract":"Software-Defined Security (SDS), which provides a flexible and centralized security solution by abstracting the security mechanisms from the hardware layer into a software layer, attracts many researchers to study the detail of this conception. One of the key challenges of SDS is how to schedule and orchestrate security appliances according to huge and heterogeneous threat information, especially when they are still lack of standardized interfaces. In this paper, we present a data driven Security Device Orchestration Framework (SDOF) for SDS. In SDOF, we put forward uniform interfaces for security devices so that they could be orchestrated by software and their data could be collected and processed centrally. The complex Structured Threat Information eXpression (STIX) ontology and corresponding tools are tailored for SDOF to standardize and centralize all data in SDS. These two achievements makes real-time dynamic orchestration possible in SDS. We also provide an orchestration scenario to demonstrate how SDOF works and evaluated its performance.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128545442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974625
Peng Xu, Ke Li, Zhanyu Ma, Yi-Zhe Song, Liang Wang, Jun Guo
Sketch-based image retrieval (SBIR) has become a prominent research topic in recent years due to the proliferation of touch screens. The problem is however very challenging for that photos and sketches are inherently modeled in different modalities. Photos are accurate (colored and textured) depictions of the real-world, whereas sketches are highly abstract (black and white) renderings often drawn from human memory. This naturally motivates us to study the effectiveness of various cross-modal retrieval methods in SBIR. However, to the best of our knowledge, all established cross-modal algorithms are designed to traverse the more conventional cross-modal gap of image and text, making their general applicableness to SBIR unclear. In this paper, we design a series of experiments to clearly illustrate circumstances under which cross-modal methods can be best utilized to solve the SBIR problem. More specifically, we choose six state-of-the-art cross-modal subspace learning approaches that were shown to work well on image-text and conduct extensive experiments on a recently released SBIR dataset. Finally, we present detailed comparative analysis of the experimental results and offer insights to benefit future research.
{"title":"Cross-modal subspace learning for sketch-based image retrieval: A comparative study","authors":"Peng Xu, Ke Li, Zhanyu Ma, Yi-Zhe Song, Liang Wang, Jun Guo","doi":"10.1109/ICNIDC.2016.7974625","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974625","url":null,"abstract":"Sketch-based image retrieval (SBIR) has become a prominent research topic in recent years due to the proliferation of touch screens. The problem is however very challenging for that photos and sketches are inherently modeled in different modalities. Photos are accurate (colored and textured) depictions of the real-world, whereas sketches are highly abstract (black and white) renderings often drawn from human memory. This naturally motivates us to study the effectiveness of various cross-modal retrieval methods in SBIR. However, to the best of our knowledge, all established cross-modal algorithms are designed to traverse the more conventional cross-modal gap of image and text, making their general applicableness to SBIR unclear. In this paper, we design a series of experiments to clearly illustrate circumstances under which cross-modal methods can be best utilized to solve the SBIR problem. More specifically, we choose six state-of-the-art cross-modal subspace learning approaches that were shown to work well on image-text and conduct extensive experiments on a recently released SBIR dataset. Finally, we present detailed comparative analysis of the experimental results and offer insights to benefit future research.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126467049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974548
Peng Wu, Shakaiba Majeed, Minsoo Ryu
In order to improve the performance of multi-threaded applications for real-time systems such as network servers and multimedia systems, asymmetric multiprocessors have been proposed. The benefits of improved performance and reduced power consumption from such architectures cannot be fully exploited unless suitable scheduling and task allocation methods are implemented at the operating system level. Our current research focuses on providing efficient scheduling algorithm for performance asymmetric multiprocessors used in real-time applications. Specifically, we present two approaches for real-time task allocation based on EDZL scheduling policy depending on the choice of speed of processors. The first approach chooses a fastest speed processor for high priority tasks. The second approach chooses a slowest speed processor for higher priority non-zero laxity tasks. We explain these two scheduling methods with examples and also derive schedulability tests for both approaches.
{"title":"Two approaches towards EDZL scheduling for performance asymmetric multiprocessors","authors":"Peng Wu, Shakaiba Majeed, Minsoo Ryu","doi":"10.1109/ICNIDC.2016.7974548","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974548","url":null,"abstract":"In order to improve the performance of multi-threaded applications for real-time systems such as network servers and multimedia systems, asymmetric multiprocessors have been proposed. The benefits of improved performance and reduced power consumption from such architectures cannot be fully exploited unless suitable scheduling and task allocation methods are implemented at the operating system level. Our current research focuses on providing efficient scheduling algorithm for performance asymmetric multiprocessors used in real-time applications. Specifically, we present two approaches for real-time task allocation based on EDZL scheduling policy depending on the choice of speed of processors. The first approach chooses a fastest speed processor for high priority tasks. The second approach chooses a slowest speed processor for higher priority non-zero laxity tasks. We explain these two scheduling methods with examples and also derive schedulability tests for both approaches.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"29 17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134527321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974545
J. Tak, Jaehoon Choi
Design of an all-textile microwave absorber for an indoor radar clear is proposed. The proposed absorber consists of two types of square ring resonator having different size, a backing ground plate, and a felt substrate with 1 mm thickness as textile material. All conductive materials are designed using conductive textiles. Different square ring resonators provide a broad absorption band by two neighboring resonance dips. The simulated results yield two absorptivity peaks greater than 96.7% and the full width at half maximum (FWHM) of 15.7% at 9.5 GHz. Also, the high absorptivity is achieved regardless of polarization angles of EM waves.
{"title":"Design of an all-textile microwave absorber for indoor radar clear","authors":"J. Tak, Jaehoon Choi","doi":"10.1109/ICNIDC.2016.7974545","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974545","url":null,"abstract":"Design of an all-textile microwave absorber for an indoor radar clear is proposed. The proposed absorber consists of two types of square ring resonator having different size, a backing ground plate, and a felt substrate with 1 mm thickness as textile material. All conductive materials are designed using conductive textiles. Different square ring resonators provide a broad absorption band by two neighboring resonance dips. The simulated results yield two absorptivity peaks greater than 96.7% and the full width at half maximum (FWHM) of 15.7% at 9.5 GHz. Also, the high absorptivity is achieved regardless of polarization angles of EM waves.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134570070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974589
Weidong Gao, Shengjie He, Gang Chuai
Zero-Forcing (ZF) algorithm is used to eliminate interference in small scale interference network. With the number of users increasing, the traditional ZF algorithm does not work effectively due to the fact that the channel matrix cannot provide sufficient dimensions to isolate interference. In this paper, we propose a Coordinated Zero-Forcing Beamforming with Clustering(CZFC) scheme to improve the defects of traditional ZF algorithm. Firstly, users are partitioned into clusters accordingto clustering rule that inter-cluster interference can almost be neglected, then CZF is applied to each cluster, respectively. Simulation results show that the proposed scheme can significantly increase system capacity, and at the same time, the proposed algorithm has low complexity. In most cases, it will be able to converge after three iterations.
{"title":"Clusteringfor coordinated zero-forcing beamformingin multi-user interference networks","authors":"Weidong Gao, Shengjie He, Gang Chuai","doi":"10.1109/ICNIDC.2016.7974589","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974589","url":null,"abstract":"Zero-Forcing (ZF) algorithm is used to eliminate interference in small scale interference network. With the number of users increasing, the traditional ZF algorithm does not work effectively due to the fact that the channel matrix cannot provide sufficient dimensions to isolate interference. In this paper, we propose a Coordinated Zero-Forcing Beamforming with Clustering(CZFC) scheme to improve the defects of traditional ZF algorithm. Firstly, users are partitioned into clusters accordingto clustering rule that inter-cluster interference can almost be neglected, then CZF is applied to each cluster, respectively. Simulation results show that the proposed scheme can significantly increase system capacity, and at the same time, the proposed algorithm has low complexity. In most cases, it will be able to converge after three iterations.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132978119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974624
Xiaoyue Cong, Lei Li
With the fast development of Social Networking Services, there has been increasingly vast amount of information published by massive network users. Given this information explosion, how to analyze the quality of User Generated Contents (UGC) automatically becomes a challenging task for researchers. To solve the problem, we need to build an effective UGC quality evaluation system. In the light of our experience, we believe that the textual content of UGC is the key factor for its quality. Hence, we focus on textual content based quality evaluation and classification instead of using UGC publishing related data, such as times being commented and forwarded in this paper. We extract various features of the textual contents based on natural language processing technologies firstly, such as word segmentation, keywords, topic model, sentence parsing, distributed word representation etc. Secondly, we build several base-learning classifiers with different features and different machine learning algorithms to assign UGC contents with four different quality labels. Then, we create the global meta-learning model based on these base classifiers to generate the final quality labels for UGC contents. We have also implemented a series of experiments based on realistic data collected from Tianya Forum and use 10-fold cross-validation to test the model. Results have shown that our proposed meta-learning model performs much better.
{"title":"UGC quality evaluation based on meta-learning and content feature analysis","authors":"Xiaoyue Cong, Lei Li","doi":"10.1109/ICNIDC.2016.7974624","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974624","url":null,"abstract":"With the fast development of Social Networking Services, there has been increasingly vast amount of information published by massive network users. Given this information explosion, how to analyze the quality of User Generated Contents (UGC) automatically becomes a challenging task for researchers. To solve the problem, we need to build an effective UGC quality evaluation system. In the light of our experience, we believe that the textual content of UGC is the key factor for its quality. Hence, we focus on textual content based quality evaluation and classification instead of using UGC publishing related data, such as times being commented and forwarded in this paper. We extract various features of the textual contents based on natural language processing technologies firstly, such as word segmentation, keywords, topic model, sentence parsing, distributed word representation etc. Secondly, we build several base-learning classifiers with different features and different machine learning algorithms to assign UGC contents with four different quality labels. Then, we create the global meta-learning model based on these base classifiers to generate the final quality labels for UGC contents. We have also implemented a series of experiments based on realistic data collected from Tianya Forum and use 10-fold cross-validation to test the model. Results have shown that our proposed meta-learning model performs much better.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131624532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974554
Xinyu Liang, Jiansong Miao
ICIC (inter-cell interference coordination) techniques are effectively applied into dense frequency reuse networks such as LTE (long term evolution). While mitigating the interference produced by nearby cells, researches only concentrate on maximum SINR or proportional fairness, without a consideration of various throughput demands. An adaptive resource allocation based on satisfaction (ARAS) algorithm is proposed not only to mitigate interferences but also to satisfy throughput demands adaptively. It utilizes eNBs (evolved-NodeBs) communications via X2 interface to allocate resources between cells. Each cell is divided into two zones: cell-edge and cell-center, of which a satisfaction is always tracked. The scheduler adjusts the resources allocation in a distributed manner related to the zone satisfaction states. Simulation results show that the proposed algorithm achieves a better satisfaction, meets different throughput demands and increases throughput fairness compared with reuse-1 model, FFR (fractional frequency reuse) and SFR (soft frequency reuse).
ICIC (inter-cell interference coordination)技术在LTE (long - term evolution)等密集频率复用网络中得到了有效的应用。在减少附近小区产生的干扰时，研究只关注最大信噪比或比例公平，而没有考虑各种吞吐量需求。提出了一种基于满足度的自适应资源分配算法(ARAS)，该算法既能减轻干扰，又能自适应满足吞吐量需求。它通过X2接口利用enb(进化节点)通信在单元之间分配资源。每个细胞被分为两个区域:细胞边缘和细胞中心，每个区域的满意度都被跟踪。调度器以与区域满意状态相关的分布式方式调整资源分配。仿真结果表明，与reuse-1模型、分数频率复用(FFR)模型和软频率复用(SFR)模型相比，该算法获得了更好的满意度，满足了不同的吞吐量需求，提高了吞吐量公平性。
{"title":"Adaptive resource allocation based on satisfaction for LTE","authors":"Xinyu Liang, Jiansong Miao","doi":"10.1109/ICNIDC.2016.7974554","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974554","url":null,"abstract":"ICIC (inter-cell interference coordination) techniques are effectively applied into dense frequency reuse networks such as LTE (long term evolution). While mitigating the interference produced by nearby cells, researches only concentrate on maximum SINR or proportional fairness, without a consideration of various throughput demands. An adaptive resource allocation based on satisfaction (ARAS) algorithm is proposed not only to mitigate interferences but also to satisfy throughput demands adaptively. It utilizes eNBs (evolved-NodeBs) communications via X2 interface to allocate resources between cells. Each cell is divided into two zones: cell-edge and cell-center, of which a satisfaction is always tracked. The scheduler adjusts the resources allocation in a distributed manner related to the zone satisfaction states. Simulation results show that the proposed algorithm achieves a better satisfaction, meets different throughput demands and increases throughput fairness compared with reuse-1 model, FFR (fractional frequency reuse) and SFR (soft frequency reuse).","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133757238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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