# Wireless Sensor Networks for Big Data Systems
## 3 Technical Approaches to WSN-Based Big Data Systems
### Data System
#### 3.4.2 Data Collection  
Although several approaches to data collection were already introduced in the terms of network system infrastructure, different algorithms will be presented in this section. This implies that data collection through static and mobile sink are not changed in the data system. However, new models and procedures are defined according to the requirements of the system. First, context-aware data mules (CADAMULE) are proposed as a solution for smart data collection in WSN [38]. In this work, [PERSON] et al. extend the context spaces modeling theory to discover new context attributes, by considering previous scenarios and events. This information is used to capture the context information. Moreover, the proposed context-aware data mule aims at delivering the data to the sink. Consequently, another approach to introduce a mobile collector is explained in [39]. This research determines the mobile sink node's trajectory by introducing an M-mobile collector based on a clustering algorithm. In the proposed scheme, mobile collectors traverse a fixed path to collect data from cluster \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Key Feature** & **Advantage** & **Disadvantage** \\ \hline
[28] & Framework based on & Open-source based & \\  & Hadoop and Storm & implementation & \\ \hline
[29] & Distributed data-centric & & \\  & storage & High energy efficiency & Deployment issues in \\  & & & real-world scenarios \\ \hline
[30] & Three-tier data mining & Urgent response &
\begin{tabular}{c} Experiments in few \\ scenarios \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of advantages and disadvantages of data systems. centroids and sensors in the clusters by multi-hop routing. [PERSON] et al. [40] proposed a four-phase mobile data collecting protocol, called mobility-assisted big data collecting protocol (MDCP). MCDP operation is largely divided into network clustering, route planning, route combination, and data collecting. During these procedures, mobile sinks need to visit all the source nodes along the constrained routes while minimizing energy consumption. However, because this problem is NP-hard, two heuristic algorithms are proposed, accordingly. The former algorithm builds routes by adding a link to the partially formed routes between two end nodes based on a measure of cost savings, while the latter algorithm follows the sequential route building algorithm. To demonstrate suitability of the proposed scheme, the performance of a mobile collector is evaluated and compared in [41]; their main objective is to evaluate expectation maximization (EM) based clustering scheme as a function of the number of mobile nodes. In addition to a mobile collector, another main issue of data collection for big data systems is energy efficiency. First, [PERSON] et al. [42] adapt sink node's mobility. A new mobile sink routing and data-gathering method through the network clustering based on a modified expectation-maximization technique is suggested. Additionally, an optimal number of clusters to minimize the energy consumption through connectivity and data request flooding model are derived. Apart from energy efficiency, the problem of a long latency caused by the mobile collector is addressed in [43]. For this problem, [PERSON] et al. propose two novel approaches: energy-efficient big data-gathering using local data collector (EEBDG-LC) and energy-efficient big data-gathering using local data collector with threshold (EEBDG-LCWT), to defeat an increased data-gathering latency of the previous algorithm named \"toward energy-efficient big data-gathering\" (TEEBD). The main issue is in placing a local data collector in every centroid of the region. Further, the amount of traffic is adjusted to prevent overwhelming by the predetermined threshold value. In the aspects of communications protocol, energy-efficient routing protocols to gather real-time data are proposed in [44]. [PERSON] et al.