Computational Overhead Analysis Sample Clauses
The Computational Overhead Analysis clause requires an assessment of the additional processing resources and time needed to implement a particular system, process, or software. In practice, this involves evaluating factors such as CPU usage, memory consumption, and potential delays introduced by new features or integrations. By mandating this analysis, the clause helps stakeholders understand the impact on system performance and ensures that any new implementation does not unduly burden existing infrastructure, thereby supporting informed decision-making and efficient resource allocation.
Computational Overhead Analysis. In this subsection, we analyze the computational overheads in terms of time taken for each step in the protocol run. To facilitate the evaluation of computation costs, we use a scale provided by Wu et al. [42]. They provided computation costs for a symmetric key operation (Th), an asymmetric key operation (TA), and an ECC point multiplication (TE) as 0.0000328 ms, 0.0214835 ms and 0.427576 ms, respectively. Although we used two fuzzy commitment functions in IoTMAKA, we consider them as the same as the hash function because of their similar nature. Table 4 and Figure 5 (a) show the computational cost comparisons of IoTMAKA and the related four protocols. Results from Table 4 show that IoTMAKA is more efficient than the protocols of ▇▇▇▇ et al; Jiang et al; and Li et al. He et al.’s protocol is slightly more efficient than IoTMAKA but their protocol lacks many functional features as shown in Table 3. He et al.’s protocol is also vulnerable to many attacks. IoTMAKA keeps the efficiency of computations by reducing computational overheads by 25% on average and achieves most functional, security, and privacy features.
Computational Overhead Analysis. In this subsection, we analyze the computational overheads in terms of time taken for each step in the protocol run. To facilitate the evaluation of computation costs, we use a scale provided by ▇▇▇▇▇ et al. [2]. They provided computation costs as in Table 3 .Table 4 shows the computational cost comparisons of M2MAKA-FS and the related protocols. Results from Table 4 show that M2MAKA-FS is more efficient than Shuai et al.’s protocol and Li et al.’s protocol. Kapito et al.’s protocol is slightly more efficient than M2MAKA-FS but their protocol lacks SK agreement with FS feature which is very important in IoT environment. Although two protocols of ▇▇▇▇▇ et al. and ▇▇▇▇ et al. are very efficient in computation cost, their protocols lack the security and privacy features as explained inTable 2. ▇▇▇▇ et al.’s protocol does not provide anonymity and unlinkability and is also not resistant to various attacks whereas ▇▇▇▇▇ et al.’s protocol does not provide unlinkability.