IP/MPLS network modeling using Bayesian networks to improve double failure recovery

Abstract

Protocols engineering of IP/MPLS networks are constantly improving with new separated features and new resilience mechanisms. In the transportation of audiovisual signals domain we must compose with multicast protocols which are designed from other scientific developments. This audiovisual traffic due to his non springy nature presents a very huge sensitivity to network recovery after a failure and these effects can be amplified by end devices (encoding, decoding and MPEG IP encapsulation). In this way when we choose between engineering solutions the unique criterion of availability is not enough, we must complete by an impact analysis on the service made by the network resilience technics. In this paper, we propose a first approach to analyze the behavior of different protocols engineering to improve selection. We propose using Bayesian networks to compare performance on different criteria and we will illustrate with two engineering models. The results focus on a real improvement of availability by choosing the adapted engineering solution.

Enclosing rail capacity/punctuality in accessibility measures: a two-step approach by using Data Envelopment Analysis and Analytic Hierarchy Process

“…The adopted movement monitoring system [26] is composed of three layers: (1) a Pebble smartwatch [27], which contains a tri-axis accelerometer and Bluetooth 4.0, for recording the user's arm movement data; (2) an Android smartphone for receiving data from Pebble and sending them to remote server after integrated with data collected from the GPS sensor and accelerometer inside the smartphone; (3) a NoSQL data search and analytic engine [28] on remote server for data storage and analysis. The structure of the collected data is as shown in Table I.…”

“…However, it is seldom verified in real SCs [21,22], since the relationships among firms in dynamic SCs are more complicated than simple one-to-one buyer-supplier connections [19,23]. The challenges imposed by the new generation of SCs [24,25,26,27] advocate for more realistic models to analyze the growing complexity of those structures. In the IRI context, it would be of benefit to assess the impact of errors in SCs characterized by more than one member in the same echelon of the chain, such as arborescent SCs [4,28].…”

“…However their availability, for volunteer computing system usage, is highly variable depending on demand, owners' behavior, their time zones, their location at home, school or work, etc. [27,12]. Consequently, the scheduler has no availability or speed guarantees.…”

“…Recent researches showed that some CPU of the grid exhibit random or auto-correlated behavior of availability or a combination of both of them [27,12]. Thereby, considering these characteristics, time series models were used in many works to predict CPU availability [8,16,4,14,25].…”

“…A literature review of the last 30 years researches on material handling equipment selection has identified 27 articles on this subject: Bookbinder and Gervais [3], Chakraborty and Banik [4], Chan, Ip and Lau [5], Cho and Egbelu [6], Chu, Egbelu and Wu [7], Fisher, Farber and Kay [8], Fonseca, Uppal and Greene [9], Gabbert and Brown [10], Hassan [11], Hassan [12], Hassan, Hogg and Smith [13], Kim and Eom [14], Kulak [15], Malmborg, Krishnakumar, Simons and Agee [16], Maniya and Bhatt [17], Matson, Mellichamph and Swaminathan [18], Mirhosseyni and Webb [19], Onut, Kara and Mert [20], Park [21], Raman, Nagalingam, Gurd and Lin [22], Sharp, et al [23], Telek [24], Trevino, Hurley, Clincy and Jang [25], Tuzkaya, Gülsün, Kahraman and Özgen [26], Velury and Kennedy [27], Welgama and Gibson [28], and Yaman [29].…”