A learning based mobile user traffic characterization for efficient resource management in cellular networks

Singh, Rajkarn; Srinivasan, Manikantan; Murthy, C. Siva Ram

doi:10.1109/ccnc.2015.7157993

Cited by 7 publications

(12 citation statements)

References 17 publications

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“…It is possible to use much more complex models, such as those defined in Singh et al 16 and Göndör et al, 17 but we use a simple model for two reasons: (1) It is sufficient to understand the basic behavior of the system; (2) the analysis is not influenced and biased by additional assumptions that are often related to a specific domain or city; They move along the two directions with equal probabilities, and their average speed is 50 km/h for vehicles and 5 km/h for pedestrians.…”

Section: Smart Avenue Scenariomentioning

confidence: 99%

“…[12][13][14] The analysis of Internet traffic generated by mobile users is an important application scenario today, 16,17,32,33 as numerous vehicles possess powerful sensing, networking, communication, and data-processing capabilities and can exchange information with each other (vehicle to vehicle, V2V) or with the roadside infrastructure such as camera and street lights (vehicle to infrastructure, V2I) over various protocols, including HTTP, SMTP, TCP/IP, WAP, and Next Generation Telematics Protocol (NGTP). [12][13][14] The analysis of Internet traffic generated by mobile users is an important application scenario today, 16,17,32,33 as numerous vehicles possess powerful sensing, networking, communication, and data-processing capabilities and can exchange information with each other (vehicle to vehicle, V2V) or with the roadside infrastructure such as camera and street lights (vehicle to infrastructure, V2I) over various protocols, including HTTP, SMTP, TCP/IP, WAP, and Next Generation Telematics Protocol (NGTP).…”

Section: Related Workmentioning

confidence: 99%

“…[12][13][14] The analysis of Internet traffic generated by mobile users is an important application scenario today, 16,17,32,33 as numerous vehicles possess powerful sensing, networking, communication, and data-processing capabilities and can exchange information with each other (vehicle to vehicle, V2V) or with the roadside infrastructure such as camera and street lights (vehicle to infrastructure, V2I) over various protocols, including HTTP, SMTP, TCP/IP, WAP, and Next Generation Telematics Protocol (NGTP). 16,17,34,35 A first example concerns to the so-called infotainment applications, such as community services (ie, point-of-interest notifications, electronic and financial services, media downloading, and parking zone management), which can require the transmission of a huge amount of data among users and road units for an efficient provisioning of such services. 16,17,34,35 A first example concerns to the so-called infotainment applications, such as community services (ie, point-of-interest notifications, electronic and financial services, media downloading, and parking zone management), which can require the transmission of a huge amount of data among users and road units for an efficient provisioning of such services.…”

Section: Related Workmentioning

confidence: 99%

“…34 A second application, recently described in Altomare et al, 36 is the accurate prediction of Internet traffic, which is useful to anticipate possible bottlenecks in some portions of the avenue, and save energy and batteries consumption by dynamically redistributing the workload between fixed and mobile devices. 16,17 The parallel analysis of the data and knowledge extracted from urban environments is a key element to enhance quality, improve performance and safety of urban services, and reduce costs and city resource consumptions. Sometimes this is also supported by the use of machine learning algorithms for traffic behavior modeling of mobile users, which is becoming a challenging issue to improve service effectiveness and efficiency.…”

Section: Related Workmentioning

confidence: 99%

“…Techniques for detecting transient faults are discussed in other works 38,39 and are generally based on the checkpoint-recovery strategy. 41,42 Some examples of more complex mobility models are defined in Singh et al 16 and In the majority of cases, faults are local in the network and only affect a few components of the network.…”

Section: Related Workmentioning

confidence: 99%

See 4 more Smart Citations

Efficient and scalable execution of smart city parallel applications

Mastroianni¹,

Cesario²,

Giordano³

2017

Concurrency and Computation

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Recent research efforts in the field of urban computing aim to develop innovative services for citizens through the application of ubiquitous and pervasive computing paradigms in urban spaces.Smart city applications need to cope with a large number of involved users and devices. Since data and objects are strictly related to the territory on which they are defined and used, it is preferable, when possible, to perform computation locally through the adoption of dispersed computing nodes such as CPU-equipped sensors. In this context, the computation related to smart city applications can be profitably and efficiently parallelized by partitioning the territory into regions and assigning the computation related to each single region to a local node. Nevertheless, the adoption of parallel computing models poses several communication and synchronization issues, especially when the number of nodes is large and the time constraints of applications are compelling. This paper presents and analyzes a parallel computing model for smart city applications in which each node needs to exchange information only with a subset of neighbor nodes, allowing the synchronization overhead to be significantly reduced. As sample application, we consider the analysis and prediction of internet traffic generated by vehicle and pedestrian devices moving on a smart avenue equipped with distributed computing nodes. This work offers a detailed performance evaluation in a number of scenarios, including uniform and nonuniform user distribution and different types of user mobility behavior. The results show that the presented computation model offers notable advantages in terms of computation efficiency and speedup, with respect to a classical all-to-all synchronization paradigm, in which the nodes need to coordinate with a central entity. KEYWORDSparallel computation, smart city, synchronization, urban computing INTRODUCTIONThe widespread diffusion of sensing technologies and large-scale computing infrastructures has enabled the collection of big and heterogeneous data that are daily produced in urban spaces. Such data are pertaining to the mobility of people or vehicles, air quality, safety issues, water/electricity consumptions, etc, and represent useful resources to improve urban services and environments. This is stimulating several research efforts in the field of urban computing, an interdisciplinary scientific field that pertains to the study and application of computing technology in urban environments. 1-3 In particular, the smart city paradigm aims to plan and design future urban territories in a more efficient way. Smart cities rely on the adoption of IT technologies, sensors, Web cams, databases, IoT systems, ubiquitous devices, wireless networks, and all those frameworks that are used for sensing cities and territories, for collecting data and for acting on the basis of the applications logic. In order to process the big amount of data being produced, smart cities are supposed to use multiple hardware and software technologies includi...

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Section: Smart Avenue Scenariomentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…[12][13][14] The analysis of Internet traffic generated by mobile users is an important application scenario today, 16,17,32,33 as numerous vehicles possess powerful sensing, networking, communication, and data-processing capabilities and can exchange information with each other (vehicle to vehicle, V2V) or with the roadside infrastructure such as camera and street lights (vehicle to infrastructure, V2I) over various protocols, including HTTP, SMTP, TCP/IP, WAP, and Next Generation Telematics Protocol (NGTP). 16,17,34,35 A first example concerns to the so-called infotainment applications, such as community services (ie, point-of-interest notifications, electronic and financial services, media downloading, and parking zone management), which can require the transmission of a huge amount of data among users and road units for an efficient provisioning of such services. 16,17,34,35 A first example concerns to the so-called infotainment applications, such as community services (ie, point-of-interest notifications, electronic and financial services, media downloading, and parking zone management), which can require the transmission of a huge amount of data among users and road units for an efficient provisioning of such services.…”

Section: Related Workmentioning

confidence: 99%