1,748 research outputs found
Graph Annotations in Modeling Complex Network Topologies
The coarsest approximation of the structure of a complex network, such as the
Internet, is a simple undirected unweighted graph. This approximation, however,
loses too much detail. In reality, objects represented by vertices and edges in
such a graph possess some non-trivial internal structure that varies across and
differentiates among distinct types of links or nodes. In this work, we
abstract such additional information as network annotations. We introduce a
network topology modeling framework that treats annotations as an extended
correlation profile of a network. Assuming we have this profile measured for a
given network, we present an algorithm to rescale it in order to construct
networks of varying size that still reproduce the original measured annotation
profile.
Using this methodology, we accurately capture the network properties
essential for realistic simulations of network applications and protocols, or
any other simulations involving complex network topologies, including modeling
and simulation of network evolution. We apply our approach to the Autonomous
System (AS) topology of the Internet annotated with business relationships
between ASs. This topology captures the large-scale structure of the Internet.
In depth understanding of this structure and tools to model it are cornerstones
of research on future Internet architectures and designs. We find that our
techniques are able to accurately capture the structure of annotation
correlations within this topology, thus reproducing a number of its important
properties in synthetically-generated random graphs
Modelling an End to End Supply Chain system Using Simulation
Within the current uncertain environment industries are predominantly faced with various challenges
resulting in greater need for skilled management and adequate technique as well as tools to manage
Supply Chains (SC) efficiently. Derived from this observation is the need to develop a generic/reusable
modelling framework that would allow firms to analyse their operational performance over time (Mackulak
and Lawrence 1998, Beamon and Chen 2001, Petrovic 2001, Lau et al. 2008, Khilwani et al. 2011, Cigollini et
al. 2014). However for this to be effectively managed the simulation modelling efforts should be directed
towards identifying the scope of the SC and the key processes performed between players.
Purpose: The research attempts to analyse trends in the field of supply chain modelling using simulation
and provide directions for future research by reviewing existing Operations Research/Operations
Management (OR/OM) literature. Structural and operational complexities as well as different business
processes within various industries are often limiting factors during modelling efforts. Successively, this
calls for the end to end (E2E) SC modelling framework where the generic processes, related policies and
techniques could be captured and supported by the powerful capabilities of simulation.
Research Approach: Following Mitroff’s (1974) scientific inquiry model and Sargent (2011) this research will
adopt simulation methodology and focus on systematic literature review in order to establish generic OR
processes and differentiate them from those which are specific to certain industries. The aim of the
research is provide a clear and informed overview of the existing literature in the area of supply chain
simulation. Therefore through a profound examination of the selected studies a conceptual model will be
design based on the selection of the most commonly used SC Processes and simulation techniques used
within those processes. The description of individual elements that make up SC processes (Hermann and
Pundoor 2006) will be defined using building blocks, which are also known as Process Categories.
Findings and Originality: This paper presents an E2E SC simulation conceptual model realised through
means of systematic literature review. Practitioners have adopted the term E2E SC while this is not
extensively featured within academic literature. The existing SC studies lack generality in regards to
capturing the entire SC within one methodological framework, which this study aims to address.
Research Impact: A systematic review of the supply chain and simulation literature takes an integrated and
holistic assessment of an E2E SC, from market-demand scenarios through order management and planning
processes, and on to manufacturing and physical distribution. Thus by providing significant advances in
understanding of the theory, methods used and applicability of supply chain simulation, this paper will
further develop a body of knowledge within this subject area.
Practical Impact: The paper will empower practitioners’ knowledge and understanding of the supply chain
processes characteristics that can be modelled using simulation. Moreover it will facilitate a selection of
specific data required for the simulation in accordance to the individual needs of the industry
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Towards delay-aware container-based Service Function Chaining in Fog Computing
Recently, the fifth-generation mobile network (5G) is getting significant attention. Empowered by Network Function Virtualization (NFV), 5G networks aim to support diverse services coming from different business verticals (e.g. Smart Cities, Automotive, etc). To fully leverage on NFV, services must be connected in a specific order forming a Service Function Chain (SFC). SFCs allow mobile operators to benefit from the high flexibility and low operational costs introduced by network softwarization. Additionally, Cloud computing is evolving towards a distributed paradigm called Fog Computing, which aims to provide a distributed cloud infrastructure by placing computational resources close to end-users. However, most SFC research only focuses on Multi-access Edge Computing (MEC) use cases where mobile operators aim to deploy services close to end-users. Bi-directional communication between Edges and Cloud are not considered in MEC, which in contrast is highly important in a Fog environment as in distributed anomaly detection services. Therefore, in this paper, we propose an SFC controller to optimize the placement of service chains in Fog environments, specifically tailored for Smart City use cases. Our approach has been validated on the Kubernetes platform, an open-source orchestrator for the automatic deployment of micro-services. Our SFC controller has been implemented as an extension to the scheduling features available in Kubernetes, enabling the efficient provisioning of container-based SFCs while optimizing resource allocation and reducing the end-to-end (E2E) latency. Results show that the proposed approach can lower the network latency up to 18% for the studied use case while conserving bandwidth when compared to the default scheduling mechanism
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