Localized Algorithm for Segregation of Critical/Non-critical Nodes in Mobile Ad Hoc and Sensor Networks

AbstractTimely segregation of connectivity-centric critical/non-critical nodes is extremely crucial in mobile ad hoc and sensor networks to assess network vulnerabilities against critical node failures and provide precautionary means for survivability. This paper presents a localized algorithm for segregation of critical/non-critical nodes (LASCNN) that opts to distinguish critical/non-critical nodes to the network connectivity based on limited topology information. Each node establishes and maintains a k-hop connection list and employ LASCNN to determine whether it is critical/non- critical. Based on the list, LASCNN marks a node as critical if its k-hop neighbor's become disconnected without the node, non-critical otherwise. Simulation experiments demonstrate the scalability of LASCNN and shows the performance is quite competitive compared to a scheme with global network information. The accuracy of LASCNN in determining critical nodes is 87% (1-hop) and 93% (2-hop) and non-critical nodes 91% (1-hop) and 93% (2-hop)

Formalizing Mobile Ad Hoc and Sensor Networks Using VDM-SL

AbstractMobile ad hoc and sensor networks (MAHSNs) are expected to become the fabric of modern societies. Despite considerable advancements, these networks are yet unable to surmount many operational challenges especially in safety-critical large-scale applications. Most of the published research focused on performance analysis of nonfunctional properties and ignore correctness of the approach which is vital in large and complex systems. This paper investigates an alternative formal specification and analysis technique for MAHSNs. We model MAHSNs as dynamic graph and employ VDM-SL for formal specification and verification of LASCNN algorithm. Constraints are put on the data where required to support validation of the formal algorithm. Pre and post conditions are defined for correct operation of communication in terms of messages. VDM-SL is used because it is a formal specification language to describe detailed examination of the system. The specification is analyzed and validated using VDM-SL toolbox

Luxury retail brands and their consumers in emerging markets: developing mobile marketing and sustaining the brand value

Understanding an individual’s self-interests remains a challenging task for consumer marketing because brands have no direct access to individual’s inner mind in order to satisfy his or her consumption-related wants, needs and expectations. In the case of luxury brands, customer service experts only seek to maintain close relationships with wealthy and elite customers, and they cannot extend the same individualized services to mass-market consumers. Among the new middle classes in emerging markets, consumers do not have strong brand attachments, but they do have high purchasing power with regard to luxuries. To bridge this gap, mobile technology could be an ideal interface through which luxury brands could enhance interactive communication and engagement with consumers. Nevertheless, research findings have revealed major discrepancies in the adoption of technology. While luxury brands have been ‘slow’ in their adoption of such technologies, consumers have adopted mobile devices as extensions of themselves in the digital world, which greatly enrich their lifestyles. Therefore, a medium should be developed to bridge this gap. The Gearbox of Exchange is proposed to help integrate the consumer’s self-interests with those of luxury brands. Through conditional access with a mutually agreed-upon exchange value to balance privacy concerns and financial risks, the consumer might be willing to share customized information with the brands with which they trust to engage. The luxury brands will benefit from the sharing of this customized information, as they can better predict an individual’s preferences and choices. This virtual engagement will revitalize customization to activate personalized services for every individual. These mutually agreed-upon interactions will develop into a mutual interdependence, a B2B2C relationship. This bond will protect brands from severe competition. More importantly, their knowledge of customized information, which is provided through their direct access to consumers’ self-interests, will fill the black box of radical behaviourism and enhance these brands’ abilities to predict individual choices. Therefore, the knowledge generated from the Gearbox of Exchange will not be meaningless to transform consumer analysis into micro marketing