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Table 1.1. Summary of Data Dissemination Protocols for Sensor Networks (supported properties or functionalities: 1. multiple sinks 2. sink mobility 3. load balancing 4. robustness 6. real time 7. in-network processing 8. query dissemination to targeted regions)
Table 1: Illustration of a Routing Table with Attribute-Value Pairs
2006
"... In PAGE 7: ... The attribute-value pairs exchanged are largely dictated by the sensing application (we show examples later). Messages are decoded using an XML schema defined in the module and a routing table as shown in Table1 is generated. The relevant data are passed to the in-network processing module and then to application-specific semantic rules that define message propagation.... ..."
Table 1: Energy consumed by the different in- network aggregation algorithms
2003
"... In PAGE 9: ... Even for the no-aggregation case, where packets are for- warded immediately after they are received, placing the sink in the center yields fresher data. Aggregation type / Scenario Corner Random Center Number of packets sent 0 100 200 300 400 500 600 None None None Periodic Periodic Periodic PHSimple PHSimple PHSimple PHAdjusted PHAdjusted PHAdjusted Figure 3: Number of data packets transmitted per round From Table1 , which shows the energy consumed by the different algorithms, we observe that, for our experimental setup, energy consumption can be re- duced to a third when data aggregation is used. Note that all aggregation schemes exhibit similar energy... ..."
Cited by 9
TABLE II AVERAGE RELATIVE RANGES (IN %) WITH NETWORKS OF DIFFERENT SIZES
Table 5.2: The elimination ordering showing eliminated vertices, added edges and in- duced clusters during the triangulation process of the network Year 2000 . The saved clusters for the junction tree are the clusters marked by an asterisk (*).
in Utilities
Table 3 lists the durations of the communications in- volved in the machine network , and puts them in perspec- tive with the processing times measured from the hyper sparc processor on a workstation, serving here as a refer- ence.
in Self-timed
"... In PAGE 9: ... Table3 : Extrapolated results ... ..."
Table IV presents the mean and variance of the residual energy and congestion of the master and bridge nodes. In- deed, these nodes are the ones that determine the network performance, since they process more data, and hence con- sume more energy than slaves.
2002
Cited by 23
Table 3: Comparison of host-network interfaces. One approach to overcome the processing bottleneck is to simplify the processing requirements. This however means moving away from multi-media applications and e cient use of the network. A more general approach is to supplement the host with increased processing power in the host- network interface. Then, the key the key factor in preventing a bottleneck will be the amount of processing done in the host versus the host-network interface. Four di erent host-network in- terfaces are compared in Table 3. The rst host-network interface in Table 3 is a contemporary LAN interface, such as an Ethernet, which performs only network framing (i.e., creating an Eth- ernet frame). The remaining protocol processing functions are done by the host. The other three host-network interfaces in Table 3 represent di erent options to be used in the Aurora network. All three will interface to a SONET link connected to an ATM switch and use hardware to per- form segmentation/reassembly at high speed. The host-network interfaces are described in order 10
1992
Cited by 10
Table 1: RAM and Code resource requirements for the three languages Tofu supports. System RAM in- cludes the ASVM and all underlying subsystems (e.g., the networking stack). For TinyScript and motlle, this means a single thread and no functions. TinySQL in- cludes set of functions and handlers needed for in- network aggregation.
"... In PAGE 7: ...2 Flexibility: Languages Tofu currently supports three languages, TinyScript, motlle and TinySQL queries. Table1 lists the resource requirements of a TinyOS image with a Tofu VM that supports one of the languages. We discuss TinySQL in Section 5.... ..."
TABLE II FAR apos;s, FRR apos;s, and EER apos;s (in %) for networks with various numbers of centers. Each network contains 2 to 16 centers contributed from the corresponding speaker and the rest are from the anti-speakers. For example, the network with 10 centers has 8 centers from the corresponding speaker and 2 from the anti-speakers, i.e. (8+2) centers.
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