Pub Date : 2018-12-01DOI: 10.1109/ANTS.2018.8710132
Anita Ramachandran, R. Adarsh, P. Pahwa, K. Anupama
Intelligent IoT-based ambient assisted living systems (AALS) have been a major research focus area in recent times. According to the studies conducted by the Govt. of India, elderly population in India has reached 8.3% of the total population [40]. Per the National Program for Health Care of the Elderly (NPHCE), the elderly population in India has tripled over the last 50 years, and is projected to increase to 33.32 million by 2021 and 300.96 million by 2051 [41]. Application of machine learning in AALS, such as fall detection, therefore, has the potential to have huge public impact. In this paper, we propose a fall detection system that takes into account not only various wearable sensor node parameter readings for a subject, but also his biological and physiological profile. The profile is used to determine a fall risk category for the subject. We performed machine learning experiments using public datasets for fall detection which included wearable sensor node readings. The algorithms were then retrained by feeding in the risk categorization of the subject, and results from this analyses are presented. The objective of the experiments was to find out the impact of a subject's risk categorization on the accuracy of fall detection. The algorithms presented here form part of a comprehensive geriatric healthcare system under development, which comprises wearable sensor nodes, coordinator nodes, an indoor localization framework and cloud-hosted application servers. A brief overview of the system capabilities is also presented.
{"title":"Machine Learning-based Fall Detection in Geriatric Healthcare Systems","authors":"Anita Ramachandran, R. Adarsh, P. Pahwa, K. Anupama","doi":"10.1109/ANTS.2018.8710132","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710132","url":null,"abstract":"Intelligent IoT-based ambient assisted living systems (AALS) have been a major research focus area in recent times. According to the studies conducted by the Govt. of India, elderly population in India has reached 8.3% of the total population [40]. Per the National Program for Health Care of the Elderly (NPHCE), the elderly population in India has tripled over the last 50 years, and is projected to increase to 33.32 million by 2021 and 300.96 million by 2051 [41]. Application of machine learning in AALS, such as fall detection, therefore, has the potential to have huge public impact. In this paper, we propose a fall detection system that takes into account not only various wearable sensor node parameter readings for a subject, but also his biological and physiological profile. The profile is used to determine a fall risk category for the subject. We performed machine learning experiments using public datasets for fall detection which included wearable sensor node readings. The algorithms were then retrained by feeding in the risk categorization of the subject, and results from this analyses are presented. The objective of the experiments was to find out the impact of a subject's risk categorization on the accuracy of fall detection. The algorithms presented here form part of a comprehensive geriatric healthcare system under development, which comprises wearable sensor nodes, coordinator nodes, an indoor localization framework and cloud-hosted application servers. A brief overview of the system capabilities is also presented.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134361263","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710096
Arijit Datta, Manish Mandloi, V. Bhatia
Massive multiple-input multiple-output (MIMO) is a core technology for 5G and beyond systems. However, symbol detection in massive MIMO requires high complexity matrix inversions. To tackle this problem, a novel and robust low complexity hybrid algorithm (HA) is proposed for uplink symbol detection in massive MIMO systems with a large number of users. Proposed HA integrates two novel techniques; non-stationary Newton iteration (NSNI) and improved sequential Richardson iteration (ISRI), which are proposed in this paper. Newton iteration (NI) is a promising technique for approximate matrix inversion, however, in this paper, Newton iteration (NI) is realized as the stationary iterative method which uses constant step size for all iterations. Consequently, NI suffers from performance-complexity trade-off. To address this issue, NSNI is proposed, which utilizes non-stationary step size that changes at each iteration. Moreover, Richardson iteration is a simple but efficient algorithm for massive MIMO detection, however, RI suffers from intersymbol interference (ISI) which is a major reason for the low performance of RI when the number of users scales up in massive MIMO system. Hence, symbols are updated sequentially to extenuate ISI in RI. In addition, to further improve the performance of RI, optimal step sizes based on each symbol-index in RI are computed and hence, an improved stationary Richardson iteration (ISRI) is introduced. Finally, to further boost bit error rate (BER), NSNI and RI are integrated into pseudo-stationary iterative HA for low complexity symbol detection in massive MIMO systems. Simulation results validate low complexity, superior BER performance and robustness of proposed HA as compared to recently reported several massive MIMO detection techniques, under both perfect and imperfect channel state information at the receiver.
{"title":"Hybrid Pseudo-stationary Iterative Detection Algorithm for Uplink Massive MIMO Systems","authors":"Arijit Datta, Manish Mandloi, V. Bhatia","doi":"10.1109/ANTS.2018.8710096","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710096","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) is a core technology for 5G and beyond systems. However, symbol detection in massive MIMO requires high complexity matrix inversions. To tackle this problem, a novel and robust low complexity hybrid algorithm (HA) is proposed for uplink symbol detection in massive MIMO systems with a large number of users. Proposed HA integrates two novel techniques; non-stationary Newton iteration (NSNI) and improved sequential Richardson iteration (ISRI), which are proposed in this paper. Newton iteration (NI) is a promising technique for approximate matrix inversion, however, in this paper, Newton iteration (NI) is realized as the stationary iterative method which uses constant step size for all iterations. Consequently, NI suffers from performance-complexity trade-off. To address this issue, NSNI is proposed, which utilizes non-stationary step size that changes at each iteration. Moreover, Richardson iteration is a simple but efficient algorithm for massive MIMO detection, however, RI suffers from intersymbol interference (ISI) which is a major reason for the low performance of RI when the number of users scales up in massive MIMO system. Hence, symbols are updated sequentially to extenuate ISI in RI. In addition, to further improve the performance of RI, optimal step sizes based on each symbol-index in RI are computed and hence, an improved stationary Richardson iteration (ISRI) is introduced. Finally, to further boost bit error rate (BER), NSNI and RI are integrated into pseudo-stationary iterative HA for low complexity symbol detection in massive MIMO systems. Simulation results validate low complexity, superior BER performance and robustness of proposed HA as compared to recently reported several massive MIMO detection techniques, under both perfect and imperfect channel state information at the receiver.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130524576","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710172
G. Rakshith, M. Rahul, G. S. Sanjay, V. NateshaB., R. R. Guddeti
The increasing utility of ubiquitous computing and dramatic shifts in the domain of Internet of Things (IoT) have generated the need to devise methods to enable the efficient storage and retrieval of data. Fog computing is the de facto paradigm most suitable to make efficient use of the edge devices and thus shifting the impetus from a centralized cloud environment to a decentralized computing paradigm. By utilizing fog resources near to the edge of the network, we can reduce the latency and the overheads involved in the processing of the data by deploying the required services on them. In this paper, we present resource provisioning framework which provisions the resources and also manages the registered services in a dynamic topology of the fog architecture. The results demonstrate that using fog computing for deploying services reduces the total service time.
{"title":"Resource Provisioning Framework for IoT Applications in Fog Computing Environment","authors":"G. Rakshith, M. Rahul, G. S. Sanjay, V. NateshaB., R. R. Guddeti","doi":"10.1109/ANTS.2018.8710172","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710172","url":null,"abstract":"The increasing utility of ubiquitous computing and dramatic shifts in the domain of Internet of Things (IoT) have generated the need to devise methods to enable the efficient storage and retrieval of data. Fog computing is the de facto paradigm most suitable to make efficient use of the edge devices and thus shifting the impetus from a centralized cloud environment to a decentralized computing paradigm. By utilizing fog resources near to the edge of the network, we can reduce the latency and the overheads involved in the processing of the data by deploying the required services on them. In this paper, we present resource provisioning framework which provisions the resources and also manages the registered services in a dynamic topology of the fog architecture. The results demonstrate that using fog computing for deploying services reduces the total service time.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126222343","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 : 2018-12-01DOI: 10.1109/ants.2018.8710077
{"title":"ANTS 2018 Message from General Co-Chairs","authors":"","doi":"10.1109/ants.2018.8710077","DOIUrl":"https://doi.org/10.1109/ants.2018.8710077","url":null,"abstract":"","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125801166","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710147
M. S. Thakur, S. Sharma, V. Bhatia
In molecular communications (MC), previous studies on various detection and modulation methods, and mitigation of inter-symbol interference (ISI) primarily are based on static transmitter and receiver nano-machines. However, in many applications including targeted drug delivery system, a dynamic behavior of communicating nano-machines is observed, and coherent detection methods are not suitable due to continuously changing channel characteristics. In this work, we have proposed a new iterative non-coherent signal detection method by considering the block-wise data symbols estimation for mobile MC, where both the transmitter and the receiver nano-machines can move or diffuse randomly along with the message molecules. We have also investigated the effect of various design parameters such as the diffusion coefficient and the distance between transmitter and receiver nano-machines for both the static and dynamic MC. The improved bit error rate performance of a MC system is observed using the proposed iterative detection method as compared to a conventional method in the presence of both ISI and counting noise.
{"title":"Noncoherent Detection for Dynamic Transmitter and Receiver in Molecular Communication","authors":"M. S. Thakur, S. Sharma, V. Bhatia","doi":"10.1109/ANTS.2018.8710147","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710147","url":null,"abstract":"In molecular communications (MC), previous studies on various detection and modulation methods, and mitigation of inter-symbol interference (ISI) primarily are based on static transmitter and receiver nano-machines. However, in many applications including targeted drug delivery system, a dynamic behavior of communicating nano-machines is observed, and coherent detection methods are not suitable due to continuously changing channel characteristics. In this work, we have proposed a new iterative non-coherent signal detection method by considering the block-wise data symbols estimation for mobile MC, where both the transmitter and the receiver nano-machines can move or diffuse randomly along with the message molecules. We have also investigated the effect of various design parameters such as the diffusion coefficient and the distance between transmitter and receiver nano-machines for both the static and dynamic MC. The improved bit error rate performance of a MC system is observed using the proposed iterative detection method as compared to a conventional method in the presence of both ISI and counting noise.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125511972","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710141
G. Abhilash, G. Divyansh
Software defined networking is a concept proposed to replace traditional networks by separating control plane and data plane. It makes the network more programmable and manageable. As there is a single point of control of the network, it is more vulnerable to intrusion. The idea is to train the network controller by machine learning algorithms to let it make the intelligent decisions automatically. In this paper, we have discussed our approach to make software defined networking more secure from various malicious attacks by making it capable of detecting and preventing such attacks.
{"title":"Intrusion Detection and Prevention in Software Defined Networking","authors":"G. Abhilash, G. Divyansh","doi":"10.1109/ANTS.2018.8710141","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710141","url":null,"abstract":"Software defined networking is a concept proposed to replace traditional networks by separating control plane and data plane. It makes the network more programmable and manageable. As there is a single point of control of the network, it is more vulnerable to intrusion. The idea is to train the network controller by machine learning algorithms to let it make the intelligent decisions automatically. In this paper, we have discussed our approach to make software defined networking more secure from various malicious attacks by making it capable of detecting and preventing such attacks.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124779025","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710136
Tanusree Chatterjee, S. Ruj, S. Bit
Now-a-days Internet has become mostly content centric. Named Data Network (NDN) has emerged as a promising candidate to cope with the use of today’s Internet. Several NDN features such as in-network caching, easier data forwarding, etc. in the routing method bring potential advantages over conventional networks. Despite the advantages, there are many challenges in NDN which are yet to be addressed. In this paper, we address two of such challenges in NDN routing: (1) Huge storage overhead in NDN router (2) High communication over-heads in the network during propagation of routing information updates. We propose changes in existing NDN routing with the aim to provide a low-overhead solution to these problems. Here instead of storing the Link State Data Base (LSDB) in all the routers, it is kept in selected special nodes only. The use of special nodes lowers down the overall storage and update overheads. We also provide supporting algorithms for data forwarding and update for grid network. The performance of the proposed method is evaluated in terms of storage and communication overheads. The results show the overheads are reduced by almost one third as compared to the existing routing method in NDN.
{"title":"Data forwarding and update propagation in grid network for NDN: A low-overhead approach","authors":"Tanusree Chatterjee, S. Ruj, S. Bit","doi":"10.1109/ANTS.2018.8710136","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710136","url":null,"abstract":"Now-a-days Internet has become mostly content centric. Named Data Network (NDN) has emerged as a promising candidate to cope with the use of today’s Internet. Several NDN features such as in-network caching, easier data forwarding, etc. in the routing method bring potential advantages over conventional networks. Despite the advantages, there are many challenges in NDN which are yet to be addressed. In this paper, we address two of such challenges in NDN routing: (1) Huge storage overhead in NDN router (2) High communication over-heads in the network during propagation of routing information updates. We propose changes in existing NDN routing with the aim to provide a low-overhead solution to these problems. Here instead of storing the Link State Data Base (LSDB) in all the routers, it is kept in selected special nodes only. The use of special nodes lowers down the overall storage and update overheads. We also provide supporting algorithms for data forwarding and update for grid network. The performance of the proposed method is evaluated in terms of storage and communication overheads. The results show the overheads are reduced by almost one third as compared to the existing routing method in NDN.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127954304","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710164
Harshul Vaishnav, A. Mathuria
Privacy-preserving license plate matching is a special case of private set intersection where the intersection result is known to only one entity. Most of the existing private license plate matching protocols rely on public key based homomorphic encryption. We propose a fast protocol for computing Hamming distance between license plates privately using symmetric homomorphic encryption. We practically analyse and compare the performance of our protocol with previous protocols which use Paillier cryptosystem.
{"title":"Fast Private License Plate Matching Using Symmetric Homomorphic Encryption","authors":"Harshul Vaishnav, A. Mathuria","doi":"10.1109/ANTS.2018.8710164","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710164","url":null,"abstract":"Privacy-preserving license plate matching is a special case of private set intersection where the intersection result is known to only one entity. Most of the existing private license plate matching protocols rely on public key based homomorphic encryption. We propose a fast protocol for computing Hamming distance between license plates privately using symmetric homomorphic encryption. We practically analyse and compare the performance of our protocol with previous protocols which use Paillier cryptosystem.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117065391","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710098
Rahul Sharma, B. Sainath
Decode-and-forward (DaF) or amplify-and-forward (AaF) relay based cooperative communication systems have been widely studied in the literature. It has been proved that relay-assisted device to device (D2D) communication can improve network performance. In this paper, a novel power adaptive, probability based relay selection policy (PA-PBRSP) is proposed for a four node relay assisted D2D cooperative communication network. In it, a power adaptive decode-and-forward (PADaF) relay whose average transmit power is constrained, adapts its transmit power and gain before encoding the signal and forward it to the destination. For the proposed policy, fading averaged symbol error rate (FASER) performance is analyzed. Specifically, analytical expressions for exact FASER and its upper bound are derived when M–ary phase shift keying (MPSK), and M–ary quadrature amplitude modulation (MQAM) schemes are employed. In order to validate the analytical results, Monte-Carlo simulations are performed for both the modulation schemes. To quantity the performance gains delivered by PA-PBRSP, the results of the proposed relaying policy are compared with the benchmark policies. Various numerical results that we obtained reveal that the proposed policy delivers FASER which is several times lower than the FASER of the benchmark relaying policies. This motivates use of PA-PBRSP policy in modern cooperative wireless networks.
{"title":"Power Constrained, Power Adaptive, Decode and Forward Relay Selection Policy Design and Performance Analysis","authors":"Rahul Sharma, B. Sainath","doi":"10.1109/ANTS.2018.8710098","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710098","url":null,"abstract":"Decode-and-forward (DaF) or amplify-and-forward (AaF) relay based cooperative communication systems have been widely studied in the literature. It has been proved that relay-assisted device to device (D2D) communication can improve network performance. In this paper, a novel power adaptive, probability based relay selection policy (PA-PBRSP) is proposed for a four node relay assisted D2D cooperative communication network. In it, a power adaptive decode-and-forward (PADaF) relay whose average transmit power is constrained, adapts its transmit power and gain before encoding the signal and forward it to the destination. For the proposed policy, fading averaged symbol error rate (FASER) performance is analyzed. Specifically, analytical expressions for exact FASER and its upper bound are derived when M–ary phase shift keying (MPSK), and M–ary quadrature amplitude modulation (MQAM) schemes are employed. In order to validate the analytical results, Monte-Carlo simulations are performed for both the modulation schemes. To quantity the performance gains delivered by PA-PBRSP, the results of the proposed relaying policy are compared with the benchmark policies. Various numerical results that we obtained reveal that the proposed policy delivers FASER which is several times lower than the FASER of the benchmark relaying policies. This motivates use of PA-PBRSP policy in modern cooperative wireless networks.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129641194","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 : 2018-12-01DOI: 10.1109/ANTS.2018.8710101
Abhishek Chakraborty, B. S. Vineeth, B. S. Manoj
Scale-free characteristics, where degree distribution of a network follows the power-law distribution, are observed in most of the existing real-world complex networks. Barabási and Albert first studied the evolution of random complex networks and observed that complex networks with node growth via preferential attachment can evolve to be scale-free. However, some complex networks such as neural networks inside the human brain, employees of an organization, and networks of closed social groups can be considered finite-sized complex networks which are relatively static with respect to the number of nodes where only the number of edges grow with time. This paper studies the gradual evolution of such finite-sized complex networks. It can be observed from our study that a finitesized complex network, with average path optimal edge growth, evolves as the following: a regular network $rightarrow a$ small-world network $rightarrow a$ scale-free network $rightarrow a$ scale-free network with the truncated degree distribution $rightarrow a$ fully connected network with unconstrained link addition. Therefore, it can be concluded that in finite-sized complex networks edge growth can result in transitional scale-free networks.
{"title":"On the Evolution of Finite-Sized Complex Networks with Constrained Link Addition","authors":"Abhishek Chakraborty, B. S. Vineeth, B. S. Manoj","doi":"10.1109/ANTS.2018.8710101","DOIUrl":"https://doi.org/10.1109/ANTS.2018.8710101","url":null,"abstract":"Scale-free characteristics, where degree distribution of a network follows the power-law distribution, are observed in most of the existing real-world complex networks. Barabási and Albert first studied the evolution of random complex networks and observed that complex networks with node growth via preferential attachment can evolve to be scale-free. However, some complex networks such as neural networks inside the human brain, employees of an organization, and networks of closed social groups can be considered finite-sized complex networks which are relatively static with respect to the number of nodes where only the number of edges grow with time. This paper studies the gradual evolution of such finite-sized complex networks. It can be observed from our study that a finitesized complex network, with average path optimal edge growth, evolves as the following: a regular network $rightarrow a$ small-world network $rightarrow a$ scale-free network $rightarrow a$ scale-free network with the truncated degree distribution $rightarrow a$ fully connected network with unconstrained link addition. Therefore, it can be concluded that in finite-sized complex networks edge growth can result in transitional scale-free networks.","PeriodicalId":273443,"journal":{"name":"2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121765803","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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