A Framework for Dynamic Network Architecture and Topology Optimization

A new paradigm in wireless network access is presented and analyzed. In this concept, certain classes of wireless terminals can be turned temporarily into an access point (AP) anytime while connected to the Internet. This creates a dynamic network architecture (DNA) since the number and location of...

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Veröffentlicht in:	IEEE/ACM transactions on networking Jg. 24; H. 2; S. 717 - 730
Hauptverfasser:	Shams Shafigh, Alireza, Lorenzo, Beatriz, Glisic, Savo, Perez-Romero, Jordi, DaSilva, Luiz A., MacKenzie, Allen B., Juha Roning
Format:	Journal Article Verlag
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Access point selection Architecture (computers) Clusters Computer networks Deoxyribonucleic acid DNA Dynamics Economic model Economic models Economics Enginyeria de la telecomunicació Genetic algorithms Network optimization Network topology Networks Optimization Ordinadors, Xarxes d Quality of service quality of service (QoS) Security Security investment Telemàtica i xarxes d'ordinadors Topology Topology reconfiguration Traffic dynamics Wireless networks Àrees temàtiques de la UPC
ISSN:	1063-6692, 1558-2566
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Abstract	A new paradigm in wireless network access is presented and analyzed. In this concept, certain classes of wireless terminals can be turned temporarily into an access point (AP) anytime while connected to the Internet. This creates a dynamic network architecture (DNA) since the number and location of these APs vary in time. In this paper, we present a framework to optimize different aspects of this architecture. First, the dynamic AP association problem is addressed with the aim to optimize the network by choosing the most convenient APs to provide the quality-of-service (QoS) levels demanded by the users with the minimum cost. Then, an economic model is developed to compensate the users for serving as APs and, thus, augmenting the network resources. The users' security investment is also taken into account in the AP selection. A preclustering process of the DNA is proposed to keep the optimization process feasible in a high dense network. To dynamically reconfigure the optimum topology and adjust it to the traffic variations, a new specific encoding of genetic algorithm (GA) is presented. Numerical results show that GA can provide the optimum topology up to two orders of magnitude faster than exhaustive search for network clusters, and the improvement significantly increases with the cluster size.
AbstractList	A new paradigm in wireless network access is presented and analyzed. In this concept, certain classes of wireless terminals can be turned temporarily into an access point (AP) anytime while connected to the Internet. This creates a dynamic network architecture (DNA) since the number and location of these APs vary in time. In this paper, we present a framework to optimize different aspects of this architecture. First, the dynamic AP association problem is addressed with the aim to optimize the network by choosing the most convenient APs to provide the quality-of-service (QoS) levels demanded by the users with the minimum cost. Then, an economic model is developed to compensate the users for serving as APs and, thus, augmenting the network resources. The users' security investment is also taken into account in the AP selection. A preclustering process of the DNA is proposed to keep the optimization process feasible in a high dense network. To dynamically reconfigure the optimum topology and adjust it to the traffic variations, a new specific encoding of genetic algorithm (GA) is presented. Numerical results show that GA can provide the optimum topology up to two orders of magnitude faster than exhaustive search for network clusters, and the improvement significantly increases with the cluster size. A new paradigm in wireless network access is presented and analyzed. In this concept, certain classes of wireless terminals can be turned temporarily into an access point (AP) anytime while connected to the Internet. This creates a dynamic network architecture (DNA) since the number and location of these APs vary in time. In this paper, we present a framework to optimize different aspects of this architecture. First, the dynamic AP association problem is addressed with the aim to optimize the network by choosing the most convenient APs to provide the quality-of-service (QoS) levels demanded by the users with the minimum cost. Then, an economic model is developed to compensate the users for serving as APs and, thus, augmenting the network resources. The users' security investment is also taken into account in the AP selection. A preclustering process of the DNA is proposed to keep the optimization process feasible in a high dense network. To dynamically reconfigure the optimum topology and adjust it to the traffic variations, a new specific encoding of genetic algorithm (GA) is presented. Numerical results show that GA can provide the optimum topology up to two orders of magnitude faster than exhaustive search for network clusters, and the improvement significantly increases with the cluster size. Peer Reviewed
Author	Perez-Romero, Jordi Glisic, Savo Lorenzo, Beatriz MacKenzie, Allen B. Shams Shafigh, Alireza DaSilva, Luiz A. Juha Roning
Author_xml	– sequence: 1 givenname: Alireza surname: Shams Shafigh fullname: Shams Shafigh, Alireza email: alireza.shamsshafigh@ee.oulu.fi organization: Dept. Commun. Eng., Univ. of Oulu, Oulu, Finland – sequence: 2 givenname: Beatriz surname: Lorenzo fullname: Lorenzo, Beatriz email: blorenzo@gti.uvigo.es organization: Univ. of Oulu, Oulu, Finland – sequence: 3 givenname: Savo surname: Glisic fullname: Glisic, Savo email: savo.glisic@ee.oulu.fi organization: Dept. Commun. Eng., Univ. of Oulu, Oulu, Finland – sequence: 4 givenname: Jordi surname: Perez-Romero fullname: Perez-Romero, Jordi email: jorperez@tsc.upc.edu organization: Dept. of Signal Theor. & Commun., Univ. Politec. de Catalunya, Barcelona, Spain – sequence: 5 givenname: Luiz A. surname: DaSilva fullname: DaSilva, Luiz A. email: ldasilva@vt.edu organization: Dept. of Electr. & Comput. Eng., Virginia Tech, Blacksburg, VA, USA – sequence: 6 givenname: Allen B. surname: MacKenzie fullname: MacKenzie, Allen B. email: mackenab@vt.edu organization: Dept. of Electr. & Comput. Eng., Virginia Tech, Blacksburg, VA, USA – sequence: 7 surname: Juha Roning fullname: Juha Roning email: jjr@ee.oulu.fi organization: Dept. of Comput. Sci. & Eng., Univ. of Oulu, Oulu, Finland
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SubjectTerms	Access point selection Architecture (computers) Clusters Computer networks Deoxyribonucleic acid DNA Dynamics Economic model Economic models Economics Enginyeria de la telecomunicació Genetic algorithms Network optimization Network topology Networks Optimization Ordinadors, Xarxes d Quality of service quality of service (QoS) Security Security investment Telemàtica i xarxes d'ordinadors Topology Topology reconfiguration Traffic dynamics Wireless networks Àrees temàtiques de la UPC
Title	A Framework for Dynamic Network Architecture and Topology Optimization
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