Rethinking routing information in mobile social networks Location-based or social-based

1. Rethinking routing information in mobile social networks Location-based or social-based Zhu, K., Li, W., & Fu, X. (2014). Rethinking routing information in mobile social networks: Location-based or social-based? Computer Communications. 指導教授：林志浩 博士 研究生：洪威岳 出處連結

2. Outline • Introduction • Related work • Preliminaries • The Soc scheme • The Loc scheme • Performance evaluation • Conclusions

3. Introduction • A mobile social network (MSN) is a network where a set of individualsinterconnect with each other based on social relationshipssuch as friendships and partnerships [19,26,22]. • In this paper, werefer to individuals (or nodes) in MSNs as mobile devices and theirsocial relationships as mutual communications of devices. • Thus data routing in MSNs relieson the movement of individuals and their encounter opportunitiesto relay data to the destination. • There are two kinds of information widely used for data routingin MSNs: location information and social information

4. Introduction • The locationinformation refers as the geographical related data, includes thegeographical coordinates [25], the distance between individuals[16] and etc., which represents the physical property of humanactivity. • The social information is defined as the inferred humanrelationship from encounter-based graph in this paper. • Accordingly, routing strategies in MSNs can be divided into two categories: the location-based routing strategies[5,17,16,25] and the social-based routing strategies [1,15,13,9,29].

5. Introduction

6. Related work- Social-based routing strategies • Bubble Rap Bubble Rap [15] considers the data routing in pocket switched network (PSN) which consists of several communities and there are social relationships among users. • SimBet SimBet [9] takes the linear combination of social similarity and social centrality as the forwarding utility to construct the data forwarding path.

7. Related work- Social-based routing strategies • Friendship-based routing considers the friendship among nodes in different time period and forwards data according to the constructed community structure. In addition, due to the fact that the social graph is constructed by the node-to-node contacts, the encounter-based data routing strategies in DTNs are also considered as social-based schemes in this paper. Prophet [18], RAPID [1]

8. Related work- Location-based routing strategies • Location-based routing strategies in wireless networks were widely studied in the past decade • They make forwarding decision according to the geographical information such as GPS coordinates and geographical distance. B. Karp proposed GPSR [16] for wireless networks. • TheMVrouting [5] combines a node’s visiting locations and encounters to calculate the probability that a node can successfully deliver a message to a destination. • Mobyspace[17] considers nodes’ mobility pattern andmodels the visiting history in a Euclidean space.

9. Preliminaries • Two nodes have social relationship if the number of their encounters exceeds a threshold (i.e. 3 encounters). • The social link between two nodes is refreshed periodically, which means the social graph is reconstructed every certain period of time (i.e. a day). • Similarly, the network maintains the GPS coordinates in the same period of time. • We assume that the buffer size of each node is large enough so that the effect of cache replacement is • omitted. Each data is made with three replicas for data routing. • Each piece of data has a certain lifespan (i.e., TTL) and when the TTL is expired, the data is discarded..

10. Preliminaries- Network model • We model the mobile social network as a graph G =(V,E,W) where V is the set of mobile nodes in the network, the set of social links is represented by E and the weights of links is depicted by W. • The social links indicate the social relations between two nodes and the weight of a link suggests the social strength. Besides, we consider the network area consists of multiple locations. • The network area is with geographic coordinates and we convert the area to a grid with squares. • Each square is considered as a location and is assigned with a unique location ID. It is represented by L = l1,l2; . . . ; ln ; ln where li means location i.

11. Preliminaries- Social information and location information • Social information: According to the encounter-based social relations among mobile devices, we model the MSN as a weighted social graph. • A node in the graph represents a mobile device. • An edge between two nodes represents the social relationship of them. • The weight of an edge corresponds to the number of encounters between two nodes. • Social information in a MSN refers as the information that either directly obtained from encounter-based social graph, or social analysis results of contact graph. • It indicates the structural status of a node in the constructed weighted graph.

12. Preliminaries- Social information and location information • Location information: To describe location information and mobility of nodes, we consider their movements as discrete time-varying events. • Each event suggests the location of a node with time label. • Specifically, an event is described by four elements: node ID, location ID, start time and time duration. • For example, if a user stay at a location for a large proportion of time, he will likely to visit the same location in the future. • The temporal location information, on the other hand, represents the instant user behavior at a certain time. • Two nodes stays closer with each other, they are more likely to encounter.

13. The Socscheme • Social-based data routing schemes handle data based on various social properties, such as social degree and the strength of social ties. • We propose a social-based representative data routing scheme in this section, which is named as Soc. • Previous research has shown that the status of nodes in a social network are uneven: some nodes are in the • central positions of the network while the others are in the edges [28]. • An example is that a small fraction of nodes occupy most of degrees in the social graph structure. • Generally speaking, forwarding data to the node who is more social active will increase the probability of data delivery.

14. The Socscheme • Based on the consideration, we propose the Soc scheme to find the most socially important nodes for routing. • The relay selection in Soc is based on a comprehensive utility calculated by several social properties. • Specifically, we address two widely used social properties: social similarity and social centrality. • Social similarity evaluates the number of common friends of two nodes, which indicates the trustiness and cohesive of social links [8,7]. We define the social similarity as follows:

15. The Socscheme

16. The Loc scheme • Location-based data forwarding strategies are usually determined by the location information like GPS coordinates and geographical distance among different nodes. • In this section, we propose a general location-based strategy called Loc for data routing in MSNs. • Nodes in the network travel from one location to another. • Generally speaking, two nodes with similar mobility pattern and close in geographical locations (i.e. they share many common visited places and their visited places are close) are more likely to meet each other in the future.

17. The Loc scheme

18. The Loc scheme • The similarity of mobility pattern measures the extent that different nodes visiting the same places. It is calculated by the time proportion that two nodes spend in the same locations [17]. • The larger time proportion that nodes stay at the same places, the more similar their mobility patterns are. • If two nodes always stay at a common location, their similarity of mobility pattern is 1. • If they share none of common places, then the similarity value will be 0.

19. The Loc scheme

20. Performance evaluation- Data traces • To conduct the experiments, we use two sets of data traces for the performance evaluation. • One group of data traces are collected from the real world and the other group is synthetic data traces. .

21. Performance evaluation- Data traces • real world data tracest. We use the MIT Reality [10], DieselNet [4] and Cabspotting [23] three real data traces to construct mobile social networks.

22. Performance evaluation- Data traces • Synthetic data traces To provide general assessing for two types of routing strategies, we produce a group of synthetic data sets to conduct the comprehensive comparisons. We use SUMO simulator [2] to mimic nodes’ movements by generating random trips during a period of two weeks. The experiment area of the synthetic trace is chosen as MIT campus and its surroundings with a rectangle covering 48 km2 (6 km 8 km). The node speed (ns) (by walking) in one trace is constant and starts from 0.5 m/s with a 0.5 m/s increment for each trace. Therefore, we generate 5 synthetic data traces with different node speeds. Meanwhile, we generate 5 synthetic data traces with different number of nodes (nn) ranging from 20 to 100.

23. Performance evaluation- Experiment setup • We use HaggleSim Emulator [14] to launch our experiments, which uses encounter entries as inputs to estimate data delivery path according to different data routing strategies. • We extract 14-day session from three data traces and synthetic data traces. • We utilize the user GPS coordinates location information and encounters as the input to construct corresponding location information and social information. • The emulator generates 1,000 messages for each round of simulations.

24. Performance evaluation- Parameter selection • We conduct experiments to decide the threshold of encounters for establishing social links and the refreshment period of the network for both contact-based social graph and GPS coordinates. • To determine the threshold of encounters for social links, we use the value 1, 3, and 7 as the threshold and evaluated the delivery ratio on different data traces.

26. Conclusions • In this paper, we study the efficiency of logical social and physical location information when they are • employed to design data routing strategies in MSNs. • We devise two general schemes for social-based and location-based routing strategies called Soc and Loc • accordingly. • The Soc scheme integrates social metrics including social degree and the number of common friends to • calculate a comprehensive routing metric. • The Loc scheme uses the geographical information like GPS coordinates and distance between nodes to • describe their geographical relation, and routes data to the nodes of closer to the destination in terms of • geographical information. • We provide comprehensive performance comparisons of Soc and Loc together with other social-based and • location-based strategies.