CHAPTER 2 Related work
In the paper [12], the author thinks that social-based routing and location-based routing are slightly different. Due to the difficulty of collecting the real trace data, we can use the social data as a substitution. If we can collect both social-based and location-based data, we can compare them with each other.
In such a variety of DTN routing researches, we focus on two types of research (1) Collecting human real movement data. (2) How to use social data to send data to the destination quickly with less resource in DTN environment. Three trace data we will discuss below do not consider the condition of what the real society is like. There are different kinds of people with different interests in the real society, and this is what makes a diverse society. The problem we focus on is
multi-destination problem like [13]. People may go to different places or do different things
depending on their jobs and interests. So if we can use a more realistic trace file that we can regard it as a tiny real society. Different kinds of nodes are moving freely in the emulator, which is closer to the real society.
2.1 Social Trace Data
2.1.1 Reality mining: MIT [14]
This experiment was carried out by MIT. The researcher gives 100 NOKIA’s smart phone to 100 students, and the experiment duration is 9 months. Students who participated in the experiment were asked to use smart phones to communicate with other students by Bluetooth, and their trace, contact time, and communicate time were recorded. Via this experiment, we can analyze and predict social activities’ relation with the subjects to know its next movement and social relations. The disadvantage of the experiment was that 75 students were from MIT Media Laboratory, and the other 25 students were from MIT Sloan business school. We think that the composition of participants can’t be a miniature of the real society.
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Figure 2: One view of the network created by MIT Reality Mining dataset
2.1.2 Cambridge [15]
This experiment was carried out by Cambridge computer lab. The researcher used the equipment named iMote to collect the real trace data. In Cambridge05, the experiment separated students into freshman and sophomore, and it also included graduate and doctoral students.
Figure 3: iMote for the experiment
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During the 11 days, 54 students used iMote equipment with Bluetooth technique, which helps to measure and record the main active area, the other students they contact, and the length of
communicate time of each student. In the future, this data can be used in social relationship experiment.
2.1.3 Infocom05, 06 [16]
This experiment was held in students and professors who attended Infocom conference in 2005 and 2006. In the beginning, every participant was given equipment named iMote. Because there were lots of different topics in the conference, every participant would go to listen to the topic they were interested in. Thus, we can know every participant’s interests and who they communicate with.
In 4 days, 98 people participated in this experiment. Through the experiment, we can know each participant’s professional specialty and whether they communicated with other people who have the same research domain., we can use participants’ communicate time to conjecture their social
relationship.
After reviewing previous research, we think we have to select the participants in order to make the trace data more similar to the real world. One of the most important things is to pick who can enroll in our experiment. All the details are described in chapter 3.
In [17], the characteristics of these datasets such as inter-contact and contact distribution have been explored in several studies [18, 19, 20], to which we refer the reader for further background information. In the trace file above, the participants are comprised of one or two particular group and it is not a general distribution pattern. Which will lead to the trace file is not general. And the trace file will be limited. What we want is a trace file that is a miniature of real society. So we will keep an eye on this while we are picking the participants to involve our experiment. And the detail will be described in chapter 3.
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2.2 Social-based in Delay-Tolerant Network
2.2.1 Social-Aware Data Diffusion in Delay Tolerant MANETs [21]
This research proposes a routing algorithm based on different interests of each node. If two nodes have similar interests, which means the similarity of interests has exceeded the threshold, then we define them as friends; otherwise, the two nodes are defined as strangers. Therefore, when two nodes meet, they will exchange interest list and data list. When their interests are similar, they are friends to each other, and they will exchange data that the carrier likes. On the other hand, if they are strangers to each other, they will diffuse data that they are not interested in the message, just like the state shown below.
Figure 4: Node infected by friend or stranger
Even if the two nodes are strangers, it doesn’t mean that their friends or people they might meet are not interested in the message. So in our routing algorithm, we give a chance to case like that. We log every node that one node has met before, and we give it a try if the log file reveals they have a high chance to meet each other again and the data also interests them. For example, node A and node B go to work at the same time in the morning, and they take the same transportation. However, they are strangers, so they may not talk to each other. It is a good time to exchange the advertising messages they got while they are on the bus. During the time they are on the bus, they can know the interests of each other, and the interests of people who they usually meet. It helps us know whether other people are good relay nodes or not.
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2.2.2 Social Network Analysis for Routing in Disconnected Delay-Tolerant MANETS [22]
It is difficult to diffuse messages in spare MANETs. All the nodes can move freely. So to find out the most efficient path is the key to this research. Previous research has conducted many theories to discover the best way to route the messages. To overcome this issue, there is Centrality, which can reveal whether the node is connected to the neighbor nodes. In other words, the node is able to know whether there is a path to the destination. They propose a new routing protocol named SimBet.
SimBet is based on the betweenness Centrality and Similarity of nodes, and it chooses the
intermediate node to help carry the messages. But the disadvantage is that all the messages tend to gather at some active nodes. Nodes, which are in relatively static state, can only transfer the
messages and are not able to get the messages they want. In our routing algorithm, we do not want a few people to carry most of the messages. We think it might lead to information starving for some nodes. We consider not only the connection between nodes but also the landmark where the node has gone before. A node can be the relay node if this node will meet some other nodes which are
interested in the message. Everyone can be the relay node depending on their movement and social relationship, and we think it is a better way to route the messages.