Efficient Information Dissemination Research Articles

A voting approach to uncover multiple influential spreaders on weighted networks

The identification of multiple spreaders on weighted complex networks is a crucial step towards efficient information diffusion, preventing epidemics spreading and etc. In this paper, we propose a novel approach WVoteRank to find multiple spreaders by extending VoteRank. VoteRank has limitations to select multiple spreaders on unweighted networks while various real networks are weighted networks such as trade networks, traffic flow networks and etc. Thus our approach WVoteRank is generalized to deal with both unweighted and weighted networks by considering both degree and weight in voting process. Experimental studies on LFR synthetic networks and real networks show that in the context of Susceptible–Infected–Recovered (SIR) propagation, WVoteRank outperforms existing states of arts methods such as weighted H-index, weighted K-shell, weighted degree centrality and weighted betweeness centrality on final affected scale. It obtains an improvement of final affected scale as much as 8.96%. Linear time complexity enables it to be applied on large networks effectively.

A Knowledge Fusion Approach for Context Awareness in Vehicular Networks

Vehicular ad-hoc networks (VANETs) are a challenging Internet of Things scenario. While research is proposing increasingly sophisticated hardware and software solutions for on-board context detection, probably high-level context information sharing has not been adequately addressed so far. This paper proposes a novel logic-based framework enabling a contextual data management and mining in VANETs. It grounds on a knowledge fusion algorithm based on nonstandard, nonmonotonic inference services in Description Logics, adopting standard Semantic Web languages. Ontology-referred context annotations produced by individual VANET nodes are merged with automatic reconciliation of inconsistencies. An efficient information dissemination protocol complements the proposal. The approach has been implemented in a vehicular network simulator and early experimental results proved its effectiveness and feasibility.

A distributed time-limited multicast algorithm for VANETs using incremental power strategy

Efficient information dissemination is the pinnacle of Vehicular Ad-hoc Networks (VANETs). In case of delay-sensitive information such as safety-related messages, it is imperative to minimize the transmission delay and increase the message reliability in VANETs. In a previous work, we proposed a Time-Limited Reliable Broadcast Incremental Power (TRBIP) algorithm, which is a centralized heuristic to reduce transmission interferences for safety message dissemination in VANETs. By reducing the total transmission energy and the number of hops, TRBIP is able to reduce the transmission interference and thus-forth maximizes the reliability. Furthermore, in TRBIP, VANETs’ features such as vehicle mobility and frequent network fragmentation are also taken into account through store-carry-and-forward and the periodic multicast tree reconstruction strategies. However, multicast tree management is hard to maintain in urban environments due to the high density of nodes in VANETs (large trees), and is affected by the city streets organizations (intersections, roundabout, ... etc.). To address the afore-mentioned issues, in this paper we propose a Distributed version of Time-Limited Reliable Broadcast Incremental Power (DTRBIP) based on a road segmentation technique. Our proposal is extended to handle both delay-sensitive and delay-tolerant applications, and also both low and high dynamic VANETs scenarios respectively urban and highway environments. The results of the simulation conducted using NS-2 simulator advocate for the efficiency of our proposed method in term of reducing the total emission energy (at least by 150 dBm), reducing the average delay by 52%, increasing the packet delivery ratio by more than to 5%, and reducing the protocol overhead up to 3%. Obtained results show a clear enhancement compared to the previous solutions (i.e, RGRP-SA, RBIP, and TRBIP).

Probabilistic flooding coverage analysis for efficient information dissemination in wireless networks

Information dissemination under Probabilistic flooding is revisited here in an attempt to realize full coverage in modern wireless networks and at the same time avoid unnecessary transmissions that waste valuable resources. Approaches like traditional flooding, are not suitable in these typically large scale and inherently dynamic environments due to the large number of transmitted information messages. Probabilistic flooding is capable of pruning unnecessary transmissions, while maintaining a large proportion of the network nodes covered. In this paper, an algebraic-based approach is employed to derive an estimation regarding the particular threshold probability value that would allow for high network coverage and reduced number of sent information messages. For the analysis’ purposes, coverage is studied here and eventually modeled as a polynomial; its higher root being related to the threshold probability. By studying this polynomial’s roots, the paper’s contribution is twofold: (i) results existing in the open literature are confirmed; and (ii) an algorithm is introduced here to estimate the threshold probability. Simulation results confirm the analytical findings and in addition, they demonstrate that the estimated value derived here regarding threshold probability, is suitable for achieving high coverage and reducing the number of transmitted information messages.

Cultural similarities and housing market linkage: evidence from OECD countries

The subprime crisis provoked a growing study on international housing market linkage. Nevertheless, the extant literature fails to explore housing price co-movements in terms of culture and a country’s responses (e.g. housing market conditions and government participation). Employing the databases on cultural similarities, housing market conditions and government participation in 18 OECD countries over 1970–2016, this article suggests that culture similarities affect house price co-movements via information dissemination efficiency and investment conduct consistency. In addition, housing supply elasticity and government participation are able to mitigate house price contagion. Hence, to withstand external shocks, countries should pay attention to the role of cultural similarities in housing price interdependence. Moreover, it is necessary to ensure that housing supply is resilient and improve government participation.

Cluster-based efficient information dissemination in dynamic networks

Dynamic network is an abstraction of networks with frequent topology changes arising from node mobility or other reasons. In this article, we first propose a dynamic network model, named ( T, L)-HiNet, to extend existing dynamic network models with clusters. ( T, L)-HiNet includes several properties defining the stability of cluster hierarchy in a dynamic network, including cluster head set, cluster member set and the connections among them. Based on ( T, L)-HiNet, we design several hierarchical information dissemination algorithms for different scenarios of dynamics. Furthermore, we extend the ( T, L)-HiNet model and corresponding algorithms in two directions, that is, stability of cluster head set and cluster size. The correctness of our algorithms is proved rigorously, and their performance is evaluated via both numerical analysis and simulations. The results show that compared with the algorithm recently proposed by Kuhn et al., our design can significantly reduce communication cost and also time cost.

The dynamics of E-government enactment in a developing country public sector organization: Evidence from Ghana

The demand for accountability, transparency and efficient service delivery by citizens in many countries is pushing many governments to adopt e-government initiatives in achieving timely and efficient information dissemination. However, research shows that many public organisations in developing countries have been slow in responding to these developments. This study investigates how organisational level factors shape e-government implementation in public organisations in a developing country. Participants were purposively selected and one-on-one in-depth interviews were used to collect data. The study identified inadequate financial and human resources, leadership support, low information communication technology (ICT) literacy as well as inadequate ICT equipment and low internet connectivity to be the factors militating against the effective implementation of the computer based technology (CBT) program at the driver and vehicle licensing authority (DVLA). The study concludes that e-government has the potential to enhance the delivery of services in public organisations if these challenges are addressed.

Network condition and application‐based data adaptive intelligent message routing in vehicular network

SummaryRecent advances in intelligent transportation systems enable a broad range of potential applications that significantly improve the vehicle and road safety and facilitate the efficient dissemination of information among the vehicles. To assist the vehicle traffic, message broadcasting is a widely adopted technique for road safety. But efficient message broadcasting is a significant issue, especially in a high network density due to the broadcast storm problem. To solve this issue, several methods are proposed to eliminate the redundant transmission of safety packets. However, they lack in restricting the broadcasting region of safety messages, and the transmissions of safety packets outside the dangerous region, and force the vehicles to unnecessary detours. This paper proposes an adaptive multimode routing protocol, network condition, and application‐based data adaptive intelligent message routing in vehicular network (NetCLEVER) that supports 2 modes of operation such as message broadcasting and intelligent routing. In message broadcasting mode, the NetCLEVER decides the dangerous region of the network by considering the changes of neighbor vehicles velocity, instead of current vehicle velocity, because a vehicle decision in velocity is interdependent with the preceding vehicles. In intelligent routing mode, the NetCLEVER exploits the cuckoo search optimization in routing by taking into account multiple routing factors such as the road topology of intersections and traffic signals and their impact on link stability, which improves the reliability of routing packets significantly. The performance evaluation illustrates that the proposed NetCLEVER improves reliable wireless communication as well as road safety in vehicular ad hoc networks.

The effect of genetic algorithm learning with a classifier system in limit order markets

By introducing a genetic algorithm with a classifier system as a learning mechanism for uninformed traders into a dynamic limit order market with asymmetric information, this paper examines the effect of the learning on traders’ trading behavior, market liquidity and efficiency. We show that the learning is effective and valuable with respect to information acquisition, forecasting, buy–sell order choice accuracies, and profit opportunity for uninformed traders. It improves information dissemination efficiency and reduces the information advantage of informed traders and hence the value of the private information. In particular, the learning and information become more valuable with higher volatility, less informed traders, and longer information lag. Furthermore, the learning makes not only uninformed but also informed traders submit more limit orders and hence increases market liquidity supply.

Information-centric dissemination protocol for safety information in vehicular ad-hoc networks

In vehicular networks, efficient safety information dissemination is a crucial issue. Unique characteristics of such an environment like highly mobility, fast topology changing, short-lived and int...

Community-Based Disaster Risk Management in the Philippines: Achievements and Challenges of the Purok System

The purok system in the Philippines is promoted as a voluntary self-organization at the sub-village level which strengthens community resilience to natural hazards. In 2011, the system received the UN Sasakawa Award and gained prominence among the practitioner community. Based on a qualitative study in the municipality of San Francisco (Cebu province) from December 2014 to March 2015, the article elaborates on the achievements and challenges of the purok system. Striking merits encompass efficient and effective information dissemination and evacuation measurements between all levels of political administration that stem from the system’s remarkable enforcement of human and social capital. This is underpinned by a clear determination of roles and responsibility that is subsumed under the concept of accountability. However, the purok system faces internal challenges of maintenance and implies profound conceptual ambiguities regarding the notion of voluntarism and capabilities that favor clientelism. Nevertheless, the purok system clearly distinguishes itself from conventional community-based disaster risk management practices and implies potentials that are highly beneficial for strengthening resilience in disaster prone areas.

Efficient service discovery in decentralized online social networks

Online social networks (OSN) have attracted millions of users worldwide over the last decade. There are a series of urgent issues faced by existing OSN such as information overload, single-point of failure and privacy concerns. The booming Internet of Things (IoT) and Cloud Computing provide paradigms for the development of decentralized OSN. In this paper, we build a self-organized decentralized OSN (SDOSN) on the overlay network of an IoT infrastructure resembling real life social graph. A user model based on homophily features is proposed considering social relationships and user interests and focuses on the key OSN functionality of efficient information dissemination. A swarm intelligence search method is also proposed to facilitate adaptive forwarding and effective service discovery. Our evaluation, performed in simulation using real-world datasets, shows that our approach achieves better performance when compared with the state-of-the-art methods in a dynamic network environment.

Real traffic-data based evaluation of vehicular traffic environment and state-of-the-art with future issues in location-centric data dissemination for VANETs

Extensive investigation has been performed in location-centric or geocast routing protocols for reliable and efficient dissemination of information in Vehicular Adhoc Networks (VANETs). Various location-centric routing protocols have been suggested in literature for road safety ITS applications considering urban and highway traffic environment. This paper characterizes vehicular environments based on real traffic data and investigates the evolution of location-centric data dissemination. The current study is carried out with three main objectives: (i) to analyze the impact of dynamic traffic environment on the design of data dissemination techniques, (ii) to characterize location-centric data dissemination in terms of functional and qualitative behavior of protocols, properties, and strengths and weaknesses, and (iii) to find some future research directions in information dissemination based on location. Vehicular traffic environments have been classified into three categories based on physical characteristics such as speed, inter-vehicular distance, neighborhood stability, traffic volume, etc. Real traffic data is considered to analyze on-road traffic environments based on the measurement of physical parameters and weather conditions. Design issues are identified in incorporating physical parameters and weather conditions into data dissemination. Functional and qualitative characteristics of location-centric techniques are explored considering urban and highway environments. Comparative analysis of location-centric techniques is carried out for both urban and highway environments individually based on some unique and common characteristics of the environments. Finally, some future research directions are identified in the area based on the detailed investigation of traffic environments and location-centric data dissemination techniques.

Public enlightenment and participation – A major contribution in mitigating climate change

Abstract Significant changes in the conventional weather pattern experienced globally have sparked enormous concerns to environmental stakeholders. Having been established that the main driver of change in our Climate is the result of anthropogenic activities which contribute to the global increase in concentration of Green House Gases (GHG), there is therefore need for effective sensitization and public awareness regarding our actions and how they contribute to the issue of Climate Change experienced globally. For this reason an effective framework needs to be designed for this purpose, hence the objective of this research. As an effective model for Public enlightenment should be one that will: enable all stakeholders gain easy access to each other to achieve efficient dissemination of information; take into consideration the geopolitical and socioeconomic nature of the region in concern; be sustainable; flexible and adaptable, this research adopted the Integrative Literature Based Research Methodology by analysing articles of renowned authors and organizations published between 1995 and 2016 to gain supportive ideas that are vital towards the design of an effective model for public enlightenment and participation in resolving Climate Change. A model fulfilling the afore mentioned qualities was designed and reviewed for its practicability and effectiveness.

High Frequency Trading and Learning

This paper introduces a limit order market model of fast and slow traders with learning to examine the effect of high frequency trading (HFT) and learning on limit order markets. We demonstrate that informed HFT makes significant profit from trading with other traders and, more importantly, it is the learning and information advantage that plays more important role than the trading speed in generating HFT profit. Overall HFT increases market liquidity consumption and supply, trading volumes, bid-ask spread, volatility and order cancellations, reduces order book depth, improves information dissemination efficiency, and generates significant event clustering effect in order flows. Interestingly, the speed of HFT is positively related to trading volume and spread and negatively related to market depth; however it has an U-shaped relation to liquidity supply and market efficiency, but an invert U-shaped relation to HFT profit and liquidity consumption. The findings provide some insight on the profitability of HFT and the current debates and puzzles about HFT.

Enhanced interworking of LTE and wi-fi direct for public safety

Mission-critical communications for public safety (PS) is of significant interest and a very high priority item for various organizations such as national regulatory agencies, telecom service providers, network vendors, device manufacturers, and third party public safety service providers. LTE has been selected as the next-generation platform to support new mission-critical realtime broadband services to the PS community [1]. To address high performance and seamless user experience, LTE networks interwork with Wi-Fi for direct communication. Wi-Fi Direct provides the ability to create groups for efficient dissemination of information needed for critical communication directly between devices. In realizing LTE for PS, it is also necessary to provide enhanced interworking between LTE and Wi-Fi for adequate emergency group communication. This article provides an overview of the PS-related efforts in 3GPP, interworking aspects of LTE, Wi-Fi and its application to PS, as well as a mechanism to enhance the interworking between the two technologies to deliver an effective solution for mission-critical communication and applications.

A Stochastic Geometry Model for Multi-Hop Highway Vehicular Communication

Carrier sense multiple access (CSMA) protocol is standardized for vehicular communication to ensure a distributed and efficient communication between vehicles. However, several vehicular applications require efficient multi-hop information dissemination. This paper exploits stochastic geometry to develop a tractable and accurate modeling framework to characterize the multi-hop transmissions for vehicular networks in a multilane highway setup. In particular, we study the tradeoffs between per-hop packet forward progress, per-hop transmission success probability, and spatial frequency reuse (SFR) efficiency imposed by different packet forwarding schemes, namely, most forward with fixed radius (MFR), the nearest with forward progress (NFP), and the random with forward progress (RFP). We also define a new performance metric, denoted as the aggregate packet progress (APP), which is a dimensionless quantity that captures the aforementioned tradeoffs. To this end, the developed model reveals the interplay between the spectrum sensing threshold ( $\boldsymbol{\rho}_{\boldsymbol{th}}$ ) of the CSMA protocol and the packet forwarding scheme. Our results show that, contrary to ALOHA networks, which always favor NFP, MFR may achieve the highest APP in CSMA networks if $\boldsymbol{\rho}_{\boldsymbol{th}}$ is properly chosen.

Information-centric dissemination protocol for safety information in vehicular ad-hoc networks

In vehicular networks, efficient safety information dissemination is a crucial issue. Unique characteristics of such an environment like highly mobility, fast topology changing, short-lived and intermittent connectivity pose challenges for safety information dissemination. Although IEEE 802.11p is standardized as an amendment to the IEEE 802.11 for connection-based wireless communication in vehicular environments (WAVE), it is still an open topic and a challenge to efficiently handle high mobility, intermittent connectivity, and spontaneous characteristics of vehicles on the roadway during wireless communication. This paper exploits information centric networking approach to design an efficient information dissemination protocol for such a challenging environment. The protocol is designed for both communication schemes in vehicular networks including vehicles-to-vehicles and vehicle-to-road. By focusing on information object itself, instead of end-to-end connection, the proposed mechanism supports fast and efficient data dissemination among multiple content consumers and multiple content providers, removing dependence on end-to-end connection between two nodes, thus improve the overall network performance. Through experimental results over different scenarios, we show that the proposed protocol achieves a significant improvement in term of the network performance compared to the conventional approach (WAVE).

Locating influential nodes in complex networks.

Understanding and controlling spreading processes in networks is an important topic with many diverse applications, including information dissemination, disease propagation and viral marketing. It is of crucial importance to identify which entities act as influential spreaders that can propagate information to a large portion of the network, in order to ensure efficient information diffusion, optimize available resources or even control the spreading. In this work, we capitalize on the properties of the K-truss decomposition, a triangle-based extension of the core decomposition of graphs, to locate individual influential nodes. Our analysis on real networks indicates that the nodes belonging to the maximal K-truss subgraph show better spreading behavior compared to previously used importance criteria, including node degree and k-core index, leading to faster and wider epidemic spreading. We further show that nodes belonging to such dense subgraphs, dominate the small set of nodes that achieve the optimal spreading in the network.

Farmers response on agricultural marketing information system in Meghalaya

Reducing knowledge gaps and sharing agricultural marketing information to farmer is an essential input for increasing productivity and boosting agricultural growth in rural areas. An attempt has been made to identify the various pattern of awareness, sources, utilization and its benefits, constraint and expectations of agricultural marketing information (AMI) among different categories of farmers in the study area of two regulated markets namely, Mawiong Regulated Market in Mylliem Block of East Khasi Hills and Garobadha Regulated Market in Selsella Block of West Garo Hills district. The sample size consisted of 120 farmers from both selected regulated market areas were selected for the study based on purposive and random sampling technique. From the findings of the research study, it was revealed that that in case of large category of sample farmers, the extent of awareness on arrivals, prices in local markets and other markets, quality/grade of produce required, post harvest handling of agricultural produce was found to be higher than small and medium size farmers. The extent of utilization of agricultural market information by different categories of sample farmers were in decision making on production, selling and post harvest handling. It was observed that the sources of agricultural market information at household level were radio, newspaper and television for small farmers. At the market level, commission agents were most predominant sources of AMI for all categories of farmers. It revealed that the market information on prices prevailed in other nearby market placed high expectations among all the categories of farmers followed by future price projections and quality wise price information. Proper integration of various agencies for adequate and efficient dissemination of vital agricultural marketing information, so that it will act as an ‘one stop solution’ for the needs of the farming community in hilly regions of Meghalaya. There is need of proper dissemination of market intelligence and information through all possible means of communication for improving the marketing efficiency.